{"id":"W2006329944","doi":"10.1037/a0027023","title":"An exemplar model of performance in the artificial grammar task: Holographic representation.","year":2012,"lang":"en","type":"article","venue":"Canadian Journal of Experimental Psychology/Revue canadienne de psychologie expérimentale","topic":"Topic Modeling","field":"Computer Science","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Natural language processing; Artificial intelligence; Grammar; Memory model; Linguistics","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":[0.001976255,0.0002812079,0.0003979512,0.0007968846,0.0001928042,0.00006818688,0.002540737,0.0002084256,0.00003611406],"category_scores_gemma":[0.00005472061,0.0002592801,0.0001745521,0.000714351,0.0003547366,0.001097488,0.0000413432,0.0005362707,0.000006886911],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003809073,"about_ca_system_score_gemma":0.0002902572,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00168752,"about_ca_topic_score_gemma":0.005859128,"domain_scores_codex":[0.9968008,0.000341839,0.0009195495,0.0004859943,0.0001625243,0.001289236],"domain_scores_gemma":[0.9972576,0.00006354284,0.000453293,0.001225666,0.00009057234,0.00090933],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0002741544,0.002495961,0.3504766,0.0000395102,0.000187131,0.0007289824,0.1183606,0.008547524,0.4453847,0.05245937,0.003398771,0.01764675],"study_design_scores_gemma":[0.01370025,0.01076444,0.5357805,0.0006297554,0.0002339606,0.01981333,0.09398994,0.07967227,0.1979713,0.03575698,0.006484571,0.005202655],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9763221,0.001510002,0.01790377,0.0008506814,0.001571131,0.0002857047,0.00001399694,0.00001607904,0.001526502],"genre_scores_gemma":[0.9837452,0.00002624517,0.0144435,0.001481116,0.0002294362,0.00003406379,0.000006885924,0.00002303092,0.00001048868],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2474134,"threshold_uncertainty_score":0.9999859,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08623202579178714,"score_gpt":0.3302681238390607,"score_spread":0.2440360980472736,"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."}}