{"id":"W2156867943","doi":"10.1002/wcs.1346","title":"Avian cognition: examples of sophisticated capabilities in space and song","year":2015,"lang":"en","type":"review","venue":"Wiley Interdisciplinary Reviews Cognitive Science","topic":"Animal Vocal Communication and Behavior","field":"Biochemistry, Genetics and Molecular Biology","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Women and Children’s Health Research Institute; University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; Alberta Ingenuity; Canada Foundation for Innovation; University of Alberta","keywords":"Categorization; Pejorative; Variety (cybernetics); Cognition; Cognitive psychology; Spatial cognition; Space (punctuation); Cognitive science; Domain (mathematical analysis); Psychology; Animal cognition; Cognitive map; Comparative psychology; Computer science; Data science; Artificial intelligence; Neuroscience","routes":{"ca_aff":true,"ca_fund":true,"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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001539607,0.0003854604,0.00123723,0.000236572,0.000145369,0.00003917913,0.0006407585,0.0001861952,0.00003810002],"category_scores_gemma":[0.0006377941,0.0003049149,0.0002155142,0.0006071505,0.002429817,0.00002273642,0.001730463,0.0002896268,0.00003509471],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005560126,"about_ca_system_score_gemma":0.0004513197,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000449841,"about_ca_topic_score_gemma":0.00002528673,"domain_scores_codex":[0.9974736,0.0004187977,0.0008455226,0.0007264462,0.0002313796,0.0003042484],"domain_scores_gemma":[0.9983526,0.00008453376,0.000484899,0.0004886684,0.0004123979,0.000176842],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00004961,0.0001911853,0.00009754816,0.004705593,0.00002274172,0.000006034209,0.0003554519,1.920892e-8,0.0004903773,0.0002778274,0.000188704,0.9936149],"study_design_scores_gemma":[0.0005969183,0.001693716,0.0004302771,0.06288802,0.0008771638,0.0002165293,0.002083311,0.000007979093,0.0002609836,0.0006924928,0.9290051,0.001247454],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0006828968,0.9946989,0.00006840025,0.00003088499,0.00006993747,0.001141574,0.000158731,0.000007969855,0.003140664],"genre_scores_gemma":[0.02423245,0.9747289,0.0002576379,0.0000250193,0.00005384667,0.0002366529,0.0002949102,0.0000238184,0.0001467065],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9923674,"threshold_uncertainty_score":0.9999403,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1288829056766993,"score_gpt":0.4235257030594054,"score_spread":0.2946427973827061,"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."}}