{"id":"W4395476790","doi":"","title":"Connecter les chapitres linguistiques de Programming Historian ?: Premières ébauches d'une table conceptuelle multilingue constituée semi-automatiquement","year":2024,"lang":"fr","type":"article","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Natural Language Processing Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"","keywords":"Computer science","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":[0.002484601,0.0006367089,0.0006921257,0.003661965,0.002697088,0.00784964,0.0009449165,0.001350955,0.01558074],"category_scores_gemma":[0.009156916,0.0007354993,0.0008149092,0.004932393,0.003693083,0.009509277,0.002647973,0.004873616,0.003753396],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003063073,"about_ca_system_score_gemma":0.003358096,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01430798,"about_ca_topic_score_gemma":0.02134806,"domain_scores_codex":[0.997586,0.001126152,0.0002462894,0.0004449886,0.0004512758,0.0001452689],"domain_scores_gemma":[0.9930013,0.00455155,0.0003011046,0.0008702712,0.001065937,0.0002097745],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0002084055,0.00006900165,0.002864233,0.0007567657,0.00004512681,0.0005055633,0.01829581,0.002033839,0.005274234,0.6013407,0.06084154,0.3077648],"study_design_scores_gemma":[0.00001171883,0.0000303047,0.001914517,0.0006109828,0.00002913771,0.000546274,0.004429565,0.003465047,0.002647639,0.08238707,0.9038853,0.00004245322],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.03231279,0.02705564,0.7923295,0.03458103,0.005199065,0.0001634541,0.002071424,0.002823307,0.1034638],"genre_scores_gemma":[0.2382349,0.03125482,0.5972369,0.005240053,0.005185947,0.0004679187,0.004789046,0.006975264,0.1106152],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01558074,"threshold_uncertainty_score":0.05212277,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01486675895577393,"score_gpt":0.2582043866782232,"score_spread":0.2433376277224493,"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."}}