{"id":"W2127473652","doi":"10.5198/jtlu.v6i1.325","title":"Microsimulation framework for urban price-taker markets","year":2013,"lang":"en","type":"article","venue":"Journal of Transport and Land Use","topic":"Transportation Planning and Optimization","field":"Social Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Clearing; Generality; Market clearing; Microsimulation; Operationalization; Computer science; Context (archaeology); Bipartite graph; Exploit; Graph; Economics; Microeconomics; Transport engineering; Theoretical computer science; Engineering","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":[0.001125648,0.0008311713,0.0009131892,0.0006364642,0.0006152162,0.00134639,0.001589637,0.001103242,0.006780642],"category_scores_gemma":[0.002805572,0.0004397492,0.00139469,0.0006093595,0.001564643,0.001997522,0.001600552,0.00134397,0.0004988807],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001665656,"about_ca_system_score_gemma":0.001284911,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00529185,"about_ca_topic_score_gemma":0.003609515,"domain_scores_codex":[0.9994593,0.0002249311,0.00002396109,0.0001196428,0.0000826554,0.00008946525],"domain_scores_gemma":[0.9989309,0.0005348711,0.0002137429,0.00008805282,0.000135061,0.00009742998],"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":[0.00001040521,0.00001632478,0.0001933566,0.0000221229,0.00001882357,0.00004582603,0.00003608268,0.6769603,0.0005197306,0.3202024,0.0004249575,0.001549681],"study_design_scores_gemma":[0.000006250925,0.00001113489,0.00004967565,0.000002781856,0.000003844379,0.000008784996,0.00001772751,0.9395891,0.0001106918,0.0593738,0.0008210561,0.000005117104],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0251168,0.0001280237,0.9666686,0.0003113185,0.00003086412,0.00005405748,0.000177226,0.000121825,0.007391315],"genre_scores_gemma":[0.8278493,0.0004924316,0.1602409,0.0001688526,0.00006269569,0.0005462661,0.0003452473,0.0001678107,0.01012636],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006780642,"threshold_uncertainty_score":0.02268356,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02017096649411896,"score_gpt":0.2786030773668319,"score_spread":0.2584321108727129,"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."}}