{"id":"W2093677625","doi":"10.3141/2133-11","title":"Calibrating a Synthetic Built Form Generator","year":2009,"lang":"en","type":"article","venue":"Transportation Research Record Journal of the Transportation Research Board","topic":"Urban Design and Spatial Analysis","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Trusted Positioning (Canada); University of Calgary","funders":"","keywords":"Metropolitan area; Computer science; Sorting; Generator (circuit theory); Process (computing); Land use; Transport engineering; Space (punctuation); Operations research; Data mining; Civil engineering; Geography; Engineering; Algorithm","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001120823,0.0004603522,0.0003146221,0.00101243,0.0003628705,0.0007394077,0.0008081486,0.0006120886,0.005641058],"category_scores_gemma":[0.003806294,0.0004460774,0.0004715529,0.0008960138,0.0003243474,0.0005391131,0.0006529012,0.0004052472,0.001559523],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009000323,"about_ca_system_score_gemma":0.0007201124,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006938011,"about_ca_topic_score_gemma":0.00694438,"domain_scores_codex":[0.9995541,0.0001321989,0.0000178208,0.0001062675,0.0001476159,0.00004190751],"domain_scores_gemma":[0.9988763,0.0003563811,0.00004807565,0.000265351,0.0003824919,0.00007135542],"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":[0.000259444,0.0002117205,0.03231758,0.0001045663,0.00005739909,0.0001818796,0.0002156722,0.8604555,0.01005613,0.003923938,0.004192113,0.08802404],"study_design_scores_gemma":[0.00003960608,0.0000792122,0.005635982,0.00001099352,0.0000113191,0.00004912833,0.00005640579,0.984646,0.004753904,0.001039792,0.00365671,0.00002097522],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4412302,0.0000504235,0.5348159,0.0001470912,0.000154183,0.0006775942,0.00383884,0.006826273,0.01225963],"genre_scores_gemma":[0.8344089,0.00003619261,0.15845,0.00004022154,0.00001092117,0.0004671979,0.003938473,0.0004561838,0.002191856],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006938011,"threshold_uncertainty_score":0.01887125,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06241663059953642,"score_gpt":0.3272099110623113,"score_spread":0.2647932804627748,"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."}}