{"id":"W2038403419","doi":"10.7202/603105ar","title":"Berber Clitic Doubling and Syntactic Extraction","year":2009,"lang":"en","type":"article","venue":"Revue québécoise de linguistique","topic":"Language, Linguistics, Cultural Analysis","field":"Arts and Humanities","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Montréal","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Clitic; Realization (probability); Linguistics; Contrast (vision); Characterization (materials science); Computer science; Natural language processing; Mathematics; Artificial intelligence; Physics; Philosophy; Statistics","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"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":[0.001109834,0.0006890771,0.0006261524,0.001818517,0.002761478,0.003477419,0.0005461895,0.0008427945,0.006344441],"category_scores_gemma":[0.0026651,0.0005368443,0.0003923302,0.001639602,0.003131249,0.006241513,0.003642714,0.001527155,0.001165176],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002387655,"about_ca_system_score_gemma":0.001339309,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003820338,"about_ca_topic_score_gemma":0.01023424,"domain_scores_codex":[0.9989484,0.0002655745,0.00007606224,0.0002291214,0.0003230594,0.0001577499],"domain_scores_gemma":[0.998321,0.0007616064,0.0002551719,0.0003257678,0.0002945372,0.00004189079],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0004454002,0.00006051366,0.01347063,0.0004967349,0.00004490231,0.002817637,0.01669308,0.0009054731,0.03550552,0.819217,0.003342557,0.1070004],"study_design_scores_gemma":[0.00004695121,0.0001452166,0.05636143,0.0004249885,0.0001310012,0.0102912,0.01399395,0.007352737,0.09626091,0.5404593,0.2742486,0.0002837304],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.610553,0.003875407,0.0758414,0.002156746,0.0002100404,0.00006016084,0.0004868033,0.0009042282,0.3059121],"genre_scores_gemma":[0.9751309,0.0006392468,0.01044047,0.0001724059,0.00005346553,0.00001345966,0.0003130979,0.0003232152,0.01291372],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006344441,"threshold_uncertainty_score":0.02122426,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01919341256695375,"score_gpt":0.2740492880134672,"score_spread":0.2548558754465134,"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."}}