{"id":"W4362730603","doi":"10.3819/ccbr.2023.180004","title":"ManyDogs Project: A Big Team Science Approach to Investigating Canine Behavior and Cognition","year":2023,"lang":"en","type":"article","venue":"Comparative Cognition & Behavior Reviews","topic":"Genetics, Bioinformatics, and Biomedical Research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":39,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"Natural Sciences and Engineering Research Council of Canada; Austrian Science Fund; City University of New York; National Science Foundation","keywords":"Comparative cognition; Animal behavior; Animal cognition; Cognition; Psychology; Cognitive science; Behavioural sciences; Cognitive psychology; Neuroscience; Biology; Zoology; Psychotherapist","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.05421555,0.001706988,0.001429063,0.00517678,0.005044462,0.007501399,0.006457601,0.003030949,0.02415418],"category_scores_gemma":[0.07443275,0.00124027,0.002659278,0.003660026,0.006935205,0.005570963,0.02023619,0.006356534,0.006098536],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003878818,"about_ca_system_score_gemma":0.01714794,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0109262,"about_ca_topic_score_gemma":0.02547801,"domain_scores_codex":[0.9647856,0.02547133,0.001137722,0.00358047,0.003824382,0.001200517],"domain_scores_gemma":[0.9051619,0.04068914,0.005830319,0.01717548,0.01666169,0.01448133],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.001747443,0.002342127,0.03807204,0.004624908,0.001603764,0.001088059,0.0541825,0.006659473,0.006395061,0.1344059,0.4441373,0.3047413],"study_design_scores_gemma":[0.001402908,0.001334336,0.03859724,0.00287972,0.0005210684,0.0003449107,0.0176217,0.009424256,0.002757134,0.2017699,0.723033,0.0003139124],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06545094,0.004219201,0.7006014,0.03669755,0.007317556,0.03225752,0.05888022,0.0126918,0.0818838],"genre_scores_gemma":[0.06855065,0.001183835,0.8315042,0.006212098,0.0008067815,0.05099496,0.02224771,0.004268012,0.01423172],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.05421555,"threshold_uncertainty_score":0.2867227,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.206822796248681,"score_gpt":0.4093317612114384,"score_spread":0.2025089649627574,"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."}}