{"id":"W4363645377","doi":"10.1037/cep0000306","title":"Scalable cognitive modelling: Putting Simon’s (1969) ant back on the beach.","year":2023,"lang":"en","type":"review","venue":"Canadian Journal of Experimental Psychology/Revue canadienne de psychologie expérimentale","topic":"Cognitive Science and Mapping","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba; McGill University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Cognition; Big data; Computer science; Cognitive science; Representation (politics); Constructive; Process (computing); Artificial intelligence; PsycINFO; Scalability; Cognitive model; Data science; Psychology; Data mining","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.007448087,0.001414792,0.001516776,0.004685354,0.0008228724,0.003905903,0.003103968,0.004829738,0.002902377],"category_scores_gemma":[0.01176619,0.0006829154,0.001260818,0.003621198,0.009418905,0.0117929,0.003089505,0.007208932,0.00224678],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00395478,"about_ca_system_score_gemma":0.005713991,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007023069,"about_ca_topic_score_gemma":0.005309883,"domain_scores_codex":[0.9957152,0.002106128,0.0002927549,0.0004130916,0.001342529,0.0001304195],"domain_scores_gemma":[0.9946474,0.003817088,0.0002116596,0.0004560172,0.0006781188,0.000189642],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00004681065,0.00002691423,0.0002387037,0.00479889,0.0001563583,0.000147048,0.0007738174,0.003011026,0.0001937069,0.5206745,0.05234309,0.4175892],"study_design_scores_gemma":[0.00001948232,0.00004010237,0.000199168,0.001923923,0.00004137491,0.0003032935,0.0001636864,0.001114597,0.0001966734,0.4347039,0.5612476,0.0000461117],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0003276507,0.9190468,0.03188014,0.03171104,0.002801066,0.0000295805,0.00006729663,0.0001436934,0.01399274],"genre_scores_gemma":[0.02432691,0.9269105,0.02822184,0.01094381,0.004372381,0.0001688721,0.0001388091,0.0001267098,0.004790146],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.007448087,"threshold_uncertainty_score":0.03938973,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2172932846120217,"score_gpt":0.3746874541142871,"score_spread":0.1573941695022654,"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."}}