{"id":"W4293232299","doi":"10.1075/lia.21003.bel","title":"L’acquisition des objets directs et indirects en français L1","year":2022,"lang":"fr","type":"article","venue":"Language Interaction and Acquisition","topic":"Natural Language Processing Techniques","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Humanities; 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":[0.001643424,0.0006746334,0.0002854567,0.001167431,0.0008024731,0.001313695,0.0003310661,0.0004499069,0.007888692],"category_scores_gemma":[0.005171267,0.0003233437,0.0002241151,0.0009110182,0.0009358671,0.0005380136,0.0008327362,0.0003988384,0.0007268501],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00195034,"about_ca_system_score_gemma":0.001384216,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.2558233,"about_ca_topic_score_gemma":0.3076575,"domain_scores_codex":[0.999119,0.0001868348,0.00008713605,0.0002398369,0.0002203356,0.0001468181],"domain_scores_gemma":[0.9922035,0.004272642,0.001146863,0.0002911213,0.001829126,0.0002568185],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0009667212,0.00009893358,0.5874191,0.000841043,0.0001476425,0.00549766,0.1158531,0.0006005913,0.101674,0.001252767,0.00186848,0.18378],"study_design_scores_gemma":[0.00001527019,0.0001940465,0.9512949,0.0001165508,0.00007489305,0.001848316,0.01929142,0.0002866813,0.009481285,0.0001041538,0.01724148,0.00005089273],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9943798,0.0004226341,0.0004666795,0.00008403123,0.000005233637,0.00001313599,0.0006351143,0.00001374935,0.003979651],"genre_scores_gemma":[0.9902489,0.0004543408,0.001718187,0.00004501321,0.000005779444,0.0000346231,0.0008957271,0.00002409514,0.006573366],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2558233,"threshold_uncertainty_score":0.5086684,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01399384440175484,"score_gpt":0.2960243486677767,"score_spread":0.2820305042660219,"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."}}