{"id":"W1908407306","doi":"10.7202/1032661ar","title":"Gender Errors in French Interlanguage","year":2015,"lang":"en","type":"article","venue":"Arborescences Revue d études françaises","topic":"Gender Studies in Language","field":"Social Sciences","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Noun; Linguistics; Grammatical gender; Vowel; Morpheme; Identification (biology); Psychology; Interlanguage; Nominalization; Noun phrase; Nasal vowel; Computer science; Philosophy","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003057617,0.0004609188,0.0003577907,0.001013662,0.000720632,0.001160629,0.0003057874,0.000575215,0.002154573],"category_scores_gemma":[0.01586051,0.0001452839,0.0002134609,0.0003810441,0.001018033,0.0006056094,0.0007167049,0.0003287826,0.0005148923],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009849111,"about_ca_system_score_gemma":0.0006424118,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02503589,"about_ca_topic_score_gemma":0.01764176,"domain_scores_codex":[0.9960929,0.001723432,0.0002237612,0.0005480177,0.001089453,0.0003224719],"domain_scores_gemma":[0.9872535,0.00725395,0.00219574,0.0006240186,0.002429051,0.0002437557],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001179676,0.0001291924,0.6509184,0.0002029422,0.00009519886,0.002556626,0.1378686,0.0007445522,0.04794513,0.001222692,0.000862286,0.1562746],"study_design_scores_gemma":[0.00001986155,0.0006573104,0.9304172,0.00009520789,0.00004883112,0.00402541,0.03949291,0.001667963,0.01432141,0.0008815234,0.008264259,0.000108042],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9970481,0.0004694804,0.0006897727,0.00008765441,0.00001826092,0.000006367401,0.0000732818,0.00002427118,0.001582826],"genre_scores_gemma":[0.9987592,0.0001269643,0.000232132,0.00002818091,0.000005557592,0.00000364004,0.00003660379,0.000009017697,0.0007988083],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02503589,"threshold_uncertainty_score":0.04978031,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06061111404182405,"score_gpt":0.3191806717320775,"score_spread":0.2585695576902535,"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."}}