{"id":"W7140289426","doi":"10.5281/zenodo.19222310","title":"La communication inclusive : des stratégies efficaces!","year":2025,"lang":"fr","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"French Language Learning Methods","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Population; Context (archaeology); Power (physics); Identification (biology)","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":[0.02214886,0.002129987,0.0008192944,0.003325625,0.004777825,0.01486976,0.001877451,0.004713438,0.01996047],"category_scores_gemma":[0.03962198,0.0007611804,0.0008999411,0.001942058,0.009862999,0.01691247,0.01195568,0.003951933,0.006971239],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002712893,"about_ca_system_score_gemma":0.00610248,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002886211,"about_ca_topic_score_gemma":0.002789434,"domain_scores_codex":[0.9601676,0.0298078,0.0009977218,0.002176799,0.005443027,0.001406922],"domain_scores_gemma":[0.972873,0.0169398,0.002127429,0.002845576,0.003498022,0.001716175],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002469604,0.0003742126,0.005951243,0.001554443,0.0001556125,0.0006178996,0.1297082,0.0009085716,0.005280266,0.3242364,0.02004828,0.5109179],"study_design_scores_gemma":[0.0001264213,0.0004501339,0.008061356,0.003100866,0.0002187488,0.001857354,0.1184407,0.003435421,0.009636047,0.3429154,0.5115225,0.0002352329],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.06454462,0.00658407,0.3585284,0.03783848,0.00104229,0.000950687,0.0003077626,0.0009663795,0.5292373],"genre_scores_gemma":[0.6881922,0.005997967,0.193491,0.005707417,0.0004773849,0.002233155,0.0002894528,0.000836181,0.1027752],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02214886,"threshold_uncertainty_score":0.1171358,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03620449223485448,"score_gpt":0.3325425181284299,"score_spread":0.2963380258935754,"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."}}