{"id":"W3186584024","doi":"10.4000/mappemonde.6284","title":"Le palmarès du Mapathon du colloque Tous (im)mobiles, tous cartographes ?","year":2021,"lang":"fr","type":"article","venue":"Mappemonde","topic":"Cultural Insights and Digital Impacts","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ministère des Transports","funders":"Agence Nationale de la Recherche","keywords":"Humanities; Art","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0002345987,0.0005305318,0.0005730633,0.0001118554,0.0005609273,0.002708193,0.0007383153,0.0003040753,0.0002270202],"category_scores_gemma":[0.0001907236,0.0004864312,0.0004333207,0.001234304,0.0003393271,0.002069719,0.0008379082,0.0003322893,0.0004655238],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001202862,"about_ca_system_score_gemma":0.0007878627,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003245122,"about_ca_topic_score_gemma":0.002578155,"domain_scores_codex":[0.9966368,0.0002217643,0.0005670479,0.0009891482,0.0005390767,0.001046164],"domain_scores_gemma":[0.997565,0.0001290882,0.0001843388,0.0009958519,0.0005006828,0.0006250356],"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":[0.00003809568,0.00143783,0.003102367,0.0002597635,0.0001448254,0.01357575,0.008075227,0.0004294258,0.008342397,0.6102436,0.2898363,0.06451448],"study_design_scores_gemma":[0.0008599384,0.000285582,0.006099427,0.0002306634,0.00004482378,0.002557064,0.0007448783,0.001729123,0.01005603,0.01659819,0.9599473,0.0008469534],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.3046553,0.0653052,0.01269476,0.05883122,0.01289272,0.001108657,0.0002979558,0.0008092746,0.5434049],"genre_scores_gemma":[0.9242069,0.001266173,0.002989076,0.003814716,0.001091931,0.00003056695,0.00006610212,0.000051481,0.06648305],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6701111,"threshold_uncertainty_score":0.9997587,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08331114519650543,"score_gpt":0.2439340564744551,"score_spread":0.1606229112779497,"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."}}