{"id":"W7034858485","doi":"","title":"Wagschal, Steven. Minding Animals in the Old and New Worlds. A Cognitive Historical Analysis. Toronto: University of Toronto Press, 2018. x + 343 pp.","year":2019,"lang":"en","type":"article","venue":"Dialnet (Universidad de la Rioja)","topic":"Philosophy, Health, and Society","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Cognition; Context (archaeology)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005141266,0.0001648552,0.0005454216,0.00003459605,0.0001025894,0.00001436388,0.0001909798,0.0002234638,0.0003289066],"category_scores_gemma":[0.00004515248,0.0001595993,0.0002104415,0.000214989,0.0001078894,0.0002791063,0.00006996698,0.000246706,0.00000536791],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001376771,"about_ca_system_score_gemma":0.0002630148,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.1116262,"about_ca_topic_score_gemma":0.02795122,"domain_scores_codex":[0.9986148,0.000277033,0.0001654237,0.0003380713,0.0002978356,0.0003067622],"domain_scores_gemma":[0.9988337,0.0004419992,0.0001505285,0.0002804965,0.00005908504,0.0002341612],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.005861241,0.001924368,0.5164731,0.001103111,0.004313252,0.001065627,0.2926341,0.00003283835,0.003370726,0.05758014,0.1023509,0.01329059],"study_design_scores_gemma":[0.007206812,0.0007271398,0.8661137,0.0002132293,0.002139673,0.00002302907,0.03455067,0.0005916218,0.00002458562,0.0004695091,0.08751185,0.000428222],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9352129,0.01518616,0.00006608949,0.001063683,0.00009781137,0.0005497616,0.00003648828,0.00002899783,0.04775813],"genre_scores_gemma":[0.9910602,0.004934959,0.0002988148,0.0002283915,0.00009200531,5.898552e-7,0.00001846583,0.00001231294,0.003354234],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3496406,"threshold_uncertainty_score":0.9897861,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01932830390944099,"score_gpt":0.2679785176376726,"score_spread":0.2486502137282316,"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."}}