{"id":"W4393032647","doi":"10.3819/ccbr.2024.190008","title":"Insights from Animals to Build Better Artificial Language Learners","year":2024,"lang":"en","type":"article","venue":"Comparative Cognition & Behavior Reviews","topic":"Fuzzy Logic and Control Systems","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Ministerio de Ciencia e Innovación","keywords":"Comparative cognition; Animal behavior; Cognitive science; Animal learning; Psychology; Animal cognition; Language acquisition; Communication; Cognitive psychology; Mathematics education; Biology; Cognition; Neuroscience; Zoology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"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":[0.001783939,0.0003755705,0.0002499488,0.0005251772,0.0005696478,0.001755252,0.0006139738,0.001292624,0.005506871],"category_scores_gemma":[0.001737178,0.0001835583,0.0002061902,0.0001951696,0.004024534,0.003165869,0.001213796,0.00231138,0.001743144],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007278888,"about_ca_system_score_gemma":0.0006503372,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008117096,"about_ca_topic_score_gemma":0.001420122,"domain_scores_codex":[0.9996229,0.000174482,0.00001718009,0.00006634929,0.00007442805,0.00004453657],"domain_scores_gemma":[0.9994521,0.0001962813,0.00005012741,0.00007778589,0.0001200425,0.0001036649],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00008764464,0.00014509,0.003021251,0.0009272222,0.00006753503,0.0003238171,0.005697068,0.001334472,0.01563402,0.7096536,0.03368412,0.2294241],"study_design_scores_gemma":[0.00002875937,0.0001421487,0.002963797,0.000370348,0.00002526231,0.0004239262,0.001382754,0.0006956717,0.002572328,0.492377,0.4989946,0.00002339856],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.1298845,0.1704982,0.1011086,0.22634,0.002608983,0.0001272738,0.0005271031,0.0006026686,0.3683026],"genre_scores_gemma":[0.7318521,0.07629138,0.1163534,0.02319259,0.001195015,0.0001860766,0.0003917767,0.0002936207,0.05024412],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005506871,"threshold_uncertainty_score":0.01842231,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1031167022308628,"score_gpt":0.3553676035971587,"score_spread":0.2522509013662959,"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."}}