{"id":"W2115388023","doi":"10.1093/ilar.44.4.259","title":"Trapping and Marking Terrestrial Mammals for Research: Integrating Ethics, Performance Criteria, Techniques, and Common Sense","year":2003,"lang":"en","type":"article","venue":"ILAR Journal","topic":"Wildlife Ecology and Conservation","field":"Environmental Science","cited_by":226,"is_retracted":false,"has_abstract":true,"ca_institutions":"Emissions Reduction Alberta","funders":"","keywords":"Context (archaeology); Trap (plumbing); Research ethics; Best practice; Computer science; Trapping; Psychology; Engineering ethics; Biology; Ecology; Political science; Environmental science; Law; Engineering","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005203003,0.00007152918,0.00009726045,0.00005066969,0.0008796216,0.0001030893,0.00005676283,0.0001261524,0.00008382452],"category_scores_gemma":[0.0005193841,0.0000641883,0.00001813937,0.00007305069,0.0002133215,0.0002703996,0.00004160254,0.0007674523,0.000001919984],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004445748,"about_ca_system_score_gemma":0.00002540775,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002784466,"about_ca_topic_score_gemma":0.00009199476,"domain_scores_codex":[0.9988413,0.0004383288,0.0001985734,0.0001379892,0.0001510807,0.0002327369],"domain_scores_gemma":[0.9993601,0.0004142981,0.00007580325,0.00006381229,0.00001508213,0.00007088138],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002709097,0.00005076551,0.8728384,0.00004727304,0.00002479264,0.00007829485,0.003211343,0.000006949514,0.01702075,0.0006104421,0.005150151,0.1006899],"study_design_scores_gemma":[0.004132922,0.001784864,0.5145057,0.0009443481,0.00007119575,0.008806666,0.003770831,0.009048529,0.02439962,0.02490788,0.4066551,0.0009723916],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9955004,0.00009529533,0.000576712,0.001645892,0.0001305479,0.0001715856,0.000001040302,0.00001146022,0.001867064],"genre_scores_gemma":[0.9907542,0.0002330601,0.008437506,0.0003114273,0.0001383792,0.00001116847,8.016483e-7,0.000007838152,0.0001055726],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4015049,"threshold_uncertainty_score":0.6765427,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1188465249943197,"score_gpt":0.3673315898728754,"score_spread":0.2484850648785557,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}