{"id":"W2228105736","doi":"","title":"Villes et croissance : Choix du lieu de residence selon le capital humain : le role des attraits urbains et de la densite des marches du travail","year":2012,"lang":"fr","type":"article","venue":"","topic":"Regional Economics and Spatial Analysis","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Humanities; Political science; Philosophy","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009063304,0.0002551682,0.0004849311,0.0009012792,0.0008258303,0.001693891,0.0006495509,0.0004528996,0.006424434],"category_scores_gemma":[0.003597077,0.000169094,0.0004772243,0.001837111,0.0009627531,0.0005573024,0.0008155128,0.0004911689,0.0003232879],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002040873,"about_ca_system_score_gemma":0.004129604,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.6876636,"about_ca_topic_score_gemma":0.8180501,"domain_scores_codex":[0.9995011,0.0001397543,0.0000190697,0.0001010071,0.0001028868,0.0001361533],"domain_scores_gemma":[0.9974112,0.00111064,0.0005397017,0.00009873338,0.00040177,0.0004379715],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00009802782,0.00003094871,0.9719525,0.00009079017,0.0001540244,0.0001480808,0.003250695,0.0004401788,0.0004151852,0.00159941,0.0003863216,0.02143385],"study_design_scores_gemma":[0.000002263275,0.00002742784,0.9932384,0.00009636605,0.0000737412,0.00006396916,0.00292709,0.0005680839,0.0001117549,0.0002828504,0.00259867,0.000009343535],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9901493,0.004091137,0.0009413061,0.0004908744,0.00001478105,0.00001606554,0.0004981905,0.00001027261,0.003788055],"genre_scores_gemma":[0.9936936,0.001612709,0.0004622922,0.0000354037,0.00001149652,0.000008439525,0.0002097095,0.000006952486,0.003959293],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6876636,"threshold_uncertainty_score":0.6283516,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02309129033005415,"score_gpt":0.2302797444903848,"score_spread":0.2071884541603307,"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."}}