{"id":"W4392744453","doi":"10.36074/logos-01.03.2024.063","title":"DEVELOPING IDEA OF UNIVERSAL GRAMMAR VIA NONINVASIVE IMAGING TECHNIQUES","year":2024,"lang":"fr","type":"article","venue":"DÉBATS SCIENTIFIQUES ET ORIENTATIONS PROSPECTIVES DU DÉVELOPPEMENT SCIENTIFIQUE","topic":"Educational Technology and Pedagogy","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"","keywords":"Computer science; Grammar; Natural language processing; Artificial intelligence; Linguistics; Philosophy","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":[0.0007868745,0.0004381711,0.0002881149,0.001046121,0.0002834052,0.0007465222,0.0008202978,0.0009758627,0.001826168],"category_scores_gemma":[0.00192462,0.0004018544,0.000322773,0.0004576264,0.001795924,0.002358175,0.0008781236,0.001983622,0.0005923542],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004111553,"about_ca_system_score_gemma":0.0004763111,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005306347,"about_ca_topic_score_gemma":0.0006503239,"domain_scores_codex":[0.9996973,0.00006261317,0.00001202899,0.0001119561,0.0000898703,0.00002619621],"domain_scores_gemma":[0.9994118,0.0002588457,0.00009446857,0.0001035481,0.00009490237,0.00003642011],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001611545,0.0001540827,0.006032108,0.0008793745,0.00007545372,0.001660399,0.0008482074,0.00206582,0.6828636,0.07647271,0.003928351,0.2248587],"study_design_scores_gemma":[0.000105398,0.00108073,0.02329721,0.0007997384,0.0002752958,0.01882359,0.0009708726,0.05292004,0.5093005,0.2891241,0.103033,0.0002695332],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.06446084,0.01018278,0.8985931,0.002960115,0.0002109132,0.0001483818,0.000420853,0.001115472,0.02190758],"genre_scores_gemma":[0.389374,0.0120419,0.5916153,0.001695591,0.0003491843,0.0005051026,0.000356025,0.0002885884,0.003774297],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.001826168,"threshold_uncertainty_score":0.006109118,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04555355053442223,"score_gpt":0.3522380522702233,"score_spread":0.3066845017358011,"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."}}