{"id":"W6963417327","doi":"10.21949/1502411","title":"North American Transportation Atlas Data (NORTAD): 1998","year":2015,"lang":"en","type":"dataset","venue":"ROSA P","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Shapefile; Geospatial analysis; Geocoding; Metadata; Geographic information system; Atlas (anatomy); Spatial analysis; Data file; Software; Geographic coordinate system","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0003643463,0.0005830991,0.0007627904,0.0002464395,0.00008906591,0.00009576971,0.00231607,0.0001691113,0.0001173087],"category_scores_gemma":[0.0001058756,0.00058651,0.00008844821,0.0009291887,0.0002531809,0.0004150229,0.0001262904,0.0006676234,0.03036756],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000194567,"about_ca_system_score_gemma":0.000541624,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.01213879,"about_ca_topic_score_gemma":0.3834992,"domain_scores_codex":[0.9964679,0.0001099982,0.0005978475,0.001152868,0.001100046,0.000571324],"domain_scores_gemma":[0.9945933,0.00005530273,0.0007925241,0.004082031,0.0001096314,0.0003671621],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00007034036,0.000123324,0.001547902,0.00007358823,0.0001173862,0.0001333258,0.00003387705,0.0000220216,0.000001722978,5.310179e-7,0.9974341,0.000441857],"study_design_scores_gemma":[0.0003551223,0.00008796609,0.009865881,0.00003139391,0.0004786013,0.00000568715,0.00002268346,0.00003062434,0.000001896033,0.000002876486,0.9884656,0.0006516902],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.002737516,0.0001165764,0.000004763435,0.00002147624,0.0004028734,0.0003962003,0.9961039,0.000195224,0.00002144867],"genre_scores_gemma":[0.0002520683,0.0001381305,0.0001910331,0.0001000823,0.00063629,0.00003468246,0.9983859,0.000161546,0.0001002415],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.3713604,"threshold_uncertainty_score":0.9996586,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04682343996735001,"score_gpt":0.3096796152223044,"score_spread":0.2628561752549544,"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."}}