{"id":"W2055627930","doi":"10.3758/s13428-012-0253-6","title":"Recoding and representation in artificial grammar learning","year":2012,"lang":"en","type":"article","venue":"Behavior Research Methods","topic":"Child and Animal Learning Development","field":"Psychology","cited_by":19,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Manitoba","funders":"","keywords":"Computer science; Encoding (memory); Natural language processing; Representation (politics); Artificial intelligence; Task (project management); Episodic memory; Grammar; Memory model; External Data Representation; Semantic memory; Machine learning; Cognition; Psychology; Linguistics; Shared memory","routes":{"ca_aff":true,"ca_fund":false,"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":[0.002217984,0.0002947396,0.0004664573,0.0006695396,0.0003031933,0.002887617,0.001400597,0.001274927,0.003572013],"category_scores_gemma":[0.02100879,0.0005114879,0.000473762,0.0006498784,0.002729375,0.005436823,0.001537875,0.001487948,0.0004523639],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006708161,"about_ca_system_score_gemma":0.0007261784,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001086236,"about_ca_topic_score_gemma":0.0008061163,"domain_scores_codex":[0.9976108,0.001442496,0.0001277873,0.000447879,0.0002636825,0.0001073105],"domain_scores_gemma":[0.9889696,0.007347582,0.0006361995,0.002183315,0.0006541013,0.0002093273],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.0004027603,0.0003236138,0.009163333,0.0003391788,0.00009406704,0.0003145153,0.004776645,0.03827532,0.0342205,0.5482625,0.001168801,0.3626588],"study_design_scores_gemma":[0.00006210845,0.0002305442,0.004587456,0.00007945519,0.00006335862,0.0005995712,0.001324788,0.2896106,0.021445,0.6763319,0.005579969,0.0000852238],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.410764,0.000392288,0.5746753,0.0008154853,0.00009611432,0.00007123657,0.0001290747,0.0007193781,0.01233721],"genre_scores_gemma":[0.8453588,0.0001559639,0.149087,0.000109129,0.00002360591,0.00009541841,0.0001745709,0.0002508973,0.004744648],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003572013,"threshold_uncertainty_score":0.0119496,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.5400207676779264,"score_gpt":0.6517631461762786,"score_spread":0.1117423784983522,"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."}}