{"id":"W4287178849","doi":"","title":"Cartographier des mouvements pour relier des territoires. L'exemple des mobilités professionnelles de Guyane","year":2021,"lang":"fr","type":"preprint","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Migration, Identity, and Health","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ministère des Transports","funders":"","keywords":"Political science; 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","sts","scholarly_communication","insufficient_payload"],"consensus_categories":["sts"],"category_scores_codex":[0.01125864,0.0006539738,0.0007650168,0.0003502649,0.005481564,0.001122732,0.001852898,0.0007522946,0.001875854],"category_scores_gemma":[0.002656217,0.0007265294,0.0005578558,0.001498961,0.003796891,0.0007484265,0.00135658,0.001011434,0.00007810502],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00121965,"about_ca_system_score_gemma":0.002066629,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.1518933,"about_ca_topic_score_gemma":0.488342,"domain_scores_codex":[0.9837446,0.01122403,0.001230902,0.001392863,0.001059546,0.001348095],"domain_scores_gemma":[0.9899992,0.00139295,0.000802661,0.001819925,0.005184402,0.000800809],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"observational","study_design_scores_codex":[0.00003159665,0.003113969,0.4057985,0.001695275,0.0002703175,0.00001468905,0.4457204,0.00007242009,0.004061093,0.08275298,0.007838564,0.0486302],"study_design_scores_gemma":[0.002199492,0.000007557506,0.4201948,0.0176558,0.0005917188,0.00004086661,0.0816206,0.002621111,0.02956493,0.364753,0.07809782,0.002652349],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9413828,0.009989526,0.0138025,0.007592354,0.0007042443,0.001041749,0.0001037125,0.0002409392,0.02514223],"genre_scores_gemma":[0.7761598,0.03463504,0.09233893,0.0002223477,0.000206539,0.0003007179,0.0006301971,0.0001068091,0.09539967],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3640998,"threshold_uncertainty_score":0.9999142,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04166690180938685,"score_gpt":0.3165851636620836,"score_spread":0.2749182618526967,"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."}}