{"id":"W1499283541","doi":"","title":"Tisser une toile d’araignée : comment construire des réseaux lexicaux en langue seconde","year":2014,"lang":"fr","type":"article","venue":"Érudit (Université de Montréal)","topic":"French Language Learning Methods","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université Laval","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":[0.006010745,0.001284698,0.0006615421,0.002556391,0.003258806,0.009553703,0.00111402,0.00380728,0.008642151],"category_scores_gemma":[0.03588333,0.0007472478,0.001278409,0.002172547,0.005015947,0.008996454,0.002140071,0.003724932,0.003167662],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003510816,"about_ca_system_score_gemma":0.005211073,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.09136648,"about_ca_topic_score_gemma":0.09173553,"domain_scores_codex":[0.9921331,0.00441798,0.0003259992,0.001047059,0.00171071,0.0003652278],"domain_scores_gemma":[0.9886183,0.007105401,0.0004654746,0.00119331,0.002284935,0.0003325674],"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":[0.0009908272,0.0002139025,0.03102932,0.001272077,0.0002705166,0.002150215,0.06533884,0.009139465,0.03133029,0.5024989,0.02557297,0.3301927],"study_design_scores_gemma":[0.0002586064,0.0004736457,0.03459493,0.0009860746,0.0003267508,0.005714977,0.06863632,0.06350731,0.04403875,0.1107446,0.6702329,0.0004851058],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.2694983,0.00434209,0.5838369,0.02508324,0.001510804,0.0003041749,0.001445434,0.004910392,0.1090687],"genre_scores_gemma":[0.7571779,0.001382182,0.1932775,0.001434707,0.000304944,0.0001415696,0.001289824,0.001122065,0.0438693],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.09136648,"threshold_uncertainty_score":0.1816693,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009722270114928086,"score_gpt":0.2254826825006613,"score_spread":0.2157604123857332,"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."}}