{"id":"W2598374252","doi":"10.4000/netcom.2545","title":"L’involution géographique : des données géosociales aux algorithmes","year":2016,"lang":"fr","type":"article","venue":"Netcom","topic":"French Urban and Social Studies","field":"Social Sciences","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"Centre de Géomatique du Québec","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":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":["sts"],"category_scores_codex":[0.000489302,0.0002908707,0.000383737,0.00008340623,0.001963479,0.00009175744,0.0003534966,0.0003847892,0.0007080907],"category_scores_gemma":[0.0003767954,0.0002304792,0.0003181201,0.0007498872,0.008184589,0.0005217224,0.0001075842,0.0001590896,0.0003743412],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007158411,"about_ca_system_score_gemma":0.0002520794,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.02332139,"about_ca_topic_score_gemma":0.04377947,"domain_scores_codex":[0.9974818,0.0004302251,0.0003419031,0.0003957376,0.0004841516,0.0008661325],"domain_scores_gemma":[0.9986548,0.0004298708,0.0001565364,0.000178121,0.0003503399,0.0002303658],"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":[0.000005978029,0.0001101852,0.01424123,0.0000299539,0.0000942186,0.000007288847,0.0111249,3.355295e-7,0.0000565612,0.5626311,0.09042527,0.321273],"study_design_scores_gemma":[0.0003602841,0.00008114691,0.03386925,0.0002465931,0.00006173924,8.038533e-7,0.002573087,0.000005118862,0.00005524215,0.2076338,0.7547678,0.0003451974],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"empirical","genre_scores_codex":[0.1197251,0.4443345,0.004058519,0.1403498,0.01600785,0.0008597269,0.0001877163,0.0006667962,0.27381],"genre_scores_gemma":[0.7020497,0.1621358,0.001962933,0.001504777,0.007765724,0.00007565451,0.000005856583,0.00005902986,0.1244405],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6643425,"threshold_uncertainty_score":0.9993358,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1264268040073053,"score_gpt":0.2830359716688682,"score_spread":0.156609167661563,"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."}}