# Animals Assured — Claude Skill Definitions (v1.0) **Package:** AA_Claude_Skills_v1.0 **Date:** April 2026 **Companion to:** AA-RES-WORKFLOW-001 v1.2, AA_Evidence_Capture.xlsx v1.1 This document…
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t Date. Additional Indications may be added by written agreement of the parties. SCHEDULE 3 FEES The fees payable by the Client to the Company for the Services are structured as follows: Milestone Trigger Amount (AUD, incl. GST) Commencement Fee Payable upon execution AUD $15,000 of this Deed Stop-Go Milestone Payable upon completion AUD $15,000 of assessments for the first two (2) Indications, provided outputs meet the Client's requirements and expectations Per Subsequent Indication Payable upon completion AUD $15,000 per of each subsequent Indication Indication assessment (beyond the first two), provided outputs meet the Client's requirements and expectations for each such Indication Payment Terms: Each invoice is payable within 14 days of issue. The Company must provide a valid tax invoice to the Client for each milestone payment. All amounts are stated in Australian dollars and are GST inclusive. Requirements and Expectations: For the purpose of Schedule 3, outputs are deemed to meet the Client's "requirements and expectations" if they are delivered in the agreed format, are scientifically sound, address the relevant Indication in sufficient depth, and are accepted in writing by the Manager. Where the Client does not accept an output, the Manager must provide written reasons within 14 days of delivery and the Company will have 14 days to revise and resubmit.
30/03/2026]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License 17510813, 2020, 6, Downloaded from https://onlinelibrary.wiley.com/doi/10.1111/avj.12930. By National Health And Medical Research Council, Wiley Online Library on [30/03/2026]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License 17510813, 2020, 6, Downloaded from https://onlinelibrary.wiley.com/doi/10.1111/avj.12930. By National Health And Medical Research Council, Wiley Online Library on [30/03/2026]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License
tor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.
tor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.
17510813, 2020, 6, Downloaded from https://onlinelibrary.wiley.com/doi/10.1111/avj.12930. By National Health And Medical Research Council, Wiley Online Library on [30/03/2026]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License 17510813, 2020, 6, Downloaded from https://onlinelibrary.wiley.com/doi/10.1111/avj.12930. By National Health And Medical Research Council, Wiley Online Library on [30/03/2026]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License 17510813, 2020, 6, Downloaded from https://onlinelibrary.wiley.com/doi/10.1111/avj.12930. By National Health And Medical Research Council, Wiley Online Library on [30/03/2026]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License 17510813, 2020, 6, Downloaded from https://onlinelibrary.wiley.com/doi/10.1111/avj.12930. By National Health And Medical Research Council, Wiley Online Library on [30/03/2026]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License 17510813, 2020, 6, Downloaded from https://onlinelibrary.wiley.com/doi/10.1111/avj.12930. By National Health And Medical Research Council, Wiley Online Library on [30/03/2026]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles
te or nursing item18,19. Multilevel binomial logistic regression (LR) Logistic Regression is a classification technique widely used for different p urposes50. In this study, we used it to compute the respective probability of each observation (pain assessment) on being classified as pain or pain-free condition. A full algorithm (Full LR), containing all predictor variables was created, and used as reference for an automated algorithm selection (glmulti::glmulti) referred to as best subsets technique. This technique finds the best candidate algorithms with optimized information criteria. To select the best subset of predictors, we considered the Bayesian information criterion (BIC), which penalizes the predictor inclusion, and therefore it contributes to finding the better fitting with less predictor’s algorithms. An exhaustive search was used to find the exact solution. The best BIC algorithm is referred to as Refined LR. Both Full LR and Refined LR followed the same procedures. Algorithms were created in the train set using stats::glm, using condition as response variable (0 = absence of pain, corresponding to M1; and 1 = presence of pain, corresponding to M2). The behavioral items from UPAPS were converted into dummy variables (0 = absence and 1 = presence of each behavior) (fastDummies::dummy_columns), and then used as predictor variables. After algorithm fitting, the event probability of occurring (Condition classification as 1) was computed for each observation in the test set (stats::predict). Wald statistics generated from the algorithms were used to rank behaviors, as proposed previously34. Canonical discriminant analysis (CDA) Canonical Discriminant Analysis is a variation of the linear discriminant analysis with the related Fisher’s linear