{"id":"W4403273356","doi":"10.4000/127kw","title":"Quantifier le genre dans les médias","year":2024,"lang":"fr","type":"article","venue":"Communication","topic":"Multiculturalism, Politics, Migration, Gender","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Agence Nationale de la Recherche","keywords":"Quantifier (linguistics); Mathematics; Art; Humanities; Philosophy; Linguistics","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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0006286143,0.0001563041,0.0001352467,0.00005618425,0.0008185431,0.0003266867,0.0006575868,0.0002392798,0.0005626114],"category_scores_gemma":[0.0001488929,0.0001615759,0.0001222178,0.0002894241,0.001253487,0.0005516387,0.0001368812,0.0003127737,0.0007974916],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008898041,"about_ca_system_score_gemma":0.0006872443,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03584895,"about_ca_topic_score_gemma":0.01627482,"domain_scores_codex":[0.998014,0.0008387873,0.0003296044,0.0002469782,0.0002581834,0.0003124892],"domain_scores_gemma":[0.9984945,0.0003117744,0.00008135618,0.0008129512,0.0001889884,0.0001104107],"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":[0.000001553767,0.00008908738,0.001179287,0.00008483371,0.00005838559,0.000001598468,0.1799596,0.00006063476,0.0007786855,0.6990001,0.09684661,0.02193962],"study_design_scores_gemma":[0.00007681566,0.000008460707,0.009126262,0.0001561528,0.00005514466,0.000004704354,0.04239279,0.004974622,0.0004742447,0.001180646,0.9413405,0.0002096816],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.380887,0.2525304,0.002087965,0.2190865,0.003275451,0.0006658657,0.0000986382,0.0004714813,0.1408967],"genre_scores_gemma":[0.7234533,0.0097929,0.001067355,0.0008600265,0.0003505891,0.00002399599,0.0001599492,0.00002782174,0.264264],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8444939,"threshold_uncertainty_score":0.9999805,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3816576378022866,"score_gpt":0.4706993275702196,"score_spread":0.08904168976793303,"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."}}