{"id":"W7067348947","doi":"","title":"MetroScope Technical Documentation Manual: An Integrated Transportation and Land Use Model Developed for Forecasting and Policy Analysis in the Portland/Vancouver Metropolitan Area","year":2001,"lang":"en","type":"article","venue":"PDXScholar  (Portland State University)","topic":"Urban Transport and Accessibility","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Metropolitan area; Documentation; Land use; Policy analysis; Land-use planning; Public policy; Qualitative analysis; Land information system; Regional planning","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":[0.0007972855,0.000965198,0.0006247843,0.001416588,0.0007093776,0.001550284,0.001507824,0.0006601986,0.1006489],"category_scores_gemma":[0.003969164,0.001029142,0.0006502638,0.002016424,0.000157826,0.001171825,0.0006101706,0.0008873626,0.03253277],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001105751,"about_ca_system_score_gemma":0.003356535,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1454011,"about_ca_topic_score_gemma":0.1841182,"domain_scores_codex":[0.9997107,0.00005850734,0.00003872399,0.00003220358,0.0001310499,0.00002871223],"domain_scores_gemma":[0.9984586,0.0004199582,0.00007760718,0.0001687751,0.0008117096,0.00006333829],"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":[0.0001331719,0.0001901347,0.009022434,0.0005347836,0.00005393885,0.0002445368,0.0002413538,0.09144294,0.001670747,0.006933515,0.7566748,0.1328577],"study_design_scores_gemma":[0.0003127471,0.00006720559,0.01010282,0.0003660083,0.00007475606,0.0002661858,0.0003578758,0.3154607,0.005087375,0.0067645,0.6610093,0.000130518],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"methods","genre_scores_codex":[0.02113911,0.0003002512,0.2155097,0.0006438366,0.0003654943,0.001155437,0.6004707,0.07438805,0.08602741],"genre_scores_gemma":[0.1269316,0.001117793,0.2607436,0.0002923387,0.00009903937,0.003550955,0.4553164,0.03000439,0.1219439],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8545989,"threshold_uncertainty_score":0.3367041,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04690397945376394,"score_gpt":0.3108995380817416,"score_spread":0.2639955586279776,"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."}}