{"id":"W4297825692","doi":"10.48550/arxiv.1508.00511","title":"Mod\\\\'{e}lisation spatiale de la formation des agglom\\\\'{e}rations dans la\\n zone alg\\\\'{e}roise","year":2015,"lang":"fr","type":"preprint","venue":"arXiv (Cornell University)","topic":"Regional Economics and Spatial Analysis","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Université Laval; Princeton University; Purdue University","keywords":"Centripetal force; Economies of agglomeration; Nonlinear system; Urban agglomeration; Economics; Economic geography; Geography; Economy; Mathematics; Physics; Mechanics; Microeconomics","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001573409,0.0005110966,0.0008557989,0.0006553658,0.000490238,0.0003519002,0.0007331746,0.000781003,0.000357684],"category_scores_gemma":[0.0001843025,0.000756224,0.0006174497,0.0006696872,0.0007291638,0.001264919,0.0004101624,0.0006045992,0.0006277466],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002540804,"about_ca_system_score_gemma":0.0003445385,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01099922,"about_ca_topic_score_gemma":0.006089063,"domain_scores_codex":[0.9970601,0.0003352853,0.0009134898,0.001076614,0.00005341011,0.0005610519],"domain_scores_gemma":[0.9970022,0.0002891413,0.001244759,0.0008264738,0.0002658462,0.0003716166],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00004379603,0.0002068565,0.02409382,0.00006820187,0.0002372087,0.00004579464,0.001661316,0.5043225,0.00001566741,0.4680361,0.0006194206,0.0006492681],"study_design_scores_gemma":[0.0008254067,0.00006409677,0.01779764,0.0000823829,0.0002062204,0.00001962302,0.0007526187,0.7161227,0.00003392025,0.2459476,0.01748274,0.0006649929],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5497144,0.0003800313,0.4232145,0.0003430157,0.0002712478,0.0002490037,0.0003585411,0.00004703981,0.0254222],"genre_scores_gemma":[0.9803804,0.00523129,0.002068462,0.00008081762,0.0002483079,0.000008554653,0.0005419005,0.00005919443,0.01138109],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.430666,"threshold_uncertainty_score":0.9994889,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08774957921677352,"score_gpt":0.178902446892615,"score_spread":0.09115286767584145,"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."}}