{"id":"W4394346704","doi":"10.6084/m9.figshare.21082522","title":"Public reports dataset for \"Proactive use of intensive aversive conditioning increases probability of retreat by coyotes\"","year":2023,"lang":"en","type":"dataset","venue":"Figshare","topic":"Memory and Neural Mechanisms","field":"Neuroscience","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Conditioning; Psychology; Statistics; Mathematics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009648035,0.001631724,0.001384468,0.001980863,0.000806384,0.001845355,0.0029454,0.001901246,0.09489343],"category_scores_gemma":[0.007575003,0.0006298865,0.001551098,0.003317529,0.0003419557,0.0008615719,0.0016642,0.001527962,0.08612064],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00123878,"about_ca_system_score_gemma":0.001900393,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04485472,"about_ca_topic_score_gemma":0.07377791,"domain_scores_codex":[0.9994524,0.00009700196,0.00006685031,0.000171514,0.0001237361,0.00008847616],"domain_scores_gemma":[0.9974725,0.0009955232,0.0003336813,0.0004807867,0.0005163529,0.0002011891],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00004305053,0.00001364433,0.0007582236,0.0005470402,0.00003568627,0.00001419401,0.00001513473,0.0001607003,0.00004002199,0.0002118803,0.9970281,0.001132459],"study_design_scores_gemma":[0.0008040078,0.0000363395,0.01739147,0.0006370639,0.0001322294,0.00009007015,0.00008982507,0.0008620465,0.0003675726,0.001467394,0.9780689,0.00005300787],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001145119,0.00004950965,0.00003082597,0.00006054236,0.00001578998,0.000004428303,0.9992484,0.0001669202,0.000309013],"genre_scores_gemma":[0.0006818592,0.00006995761,0.0001895277,0.00005374584,0.000009597935,0.00009540183,0.9978549,0.0000815977,0.000963371],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.09489343,"threshold_uncertainty_score":0.3174501,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3951236128389763,"score_gpt":0.3478020739337343,"score_spread":0.04732153890524199,"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."}}