{"id":"W2145604114","doi":"10.1139/l06-127","title":"Genetically-optimized origin-destination estimation (GOODE) model: application to regional commodity movements in Ontario","year":2007,"lang":"en","type":"article","venue":"Canadian Journal of Civil Engineering","topic":"Transportation Planning and Optimization","field":"Social Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Estimation; Commodity; Matrix (chemical analysis); Operations research; Mathematics; Economics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"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":[0.0006619788,0.0005229372,0.0004760031,0.0005015573,0.0007795986,0.0006305033,0.001014946,0.0006636863,0.001499332],"category_scores_gemma":[0.002682565,0.000266006,0.0004253547,0.001205955,0.0006892886,0.0004304131,0.0005346121,0.0003999673,0.00009871178],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.007396261,"about_ca_system_score_gemma":0.004732913,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8016022,"about_ca_topic_score_gemma":0.7494107,"domain_scores_codex":[0.9997639,0.00007666551,0.00001006306,0.00006124204,0.00004474201,0.00004351828],"domain_scores_gemma":[0.999382,0.0003364187,0.00007700179,0.00002868776,0.0001513479,0.00002460459],"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":[0.00001935506,0.000008449876,0.004894092,0.00001351511,0.00001257413,0.0000769074,0.00005416078,0.9884077,0.0001333805,0.001713397,0.0001977151,0.004468765],"study_design_scores_gemma":[0.00001025319,0.000010273,0.002762982,0.000002779941,0.000008865719,0.00001088111,0.00005220113,0.9957827,0.0001171056,0.0007966743,0.0004381675,0.000007219577],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7957863,0.0001873433,0.1898756,0.0006574033,0.00001989505,0.0001522913,0.001314805,0.0002983656,0.01170811],"genre_scores_gemma":[0.9689342,0.00008763179,0.02680711,0.00001519391,0.000002914937,0.000049911,0.000476941,0.00002125378,0.003604955],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1983978,"threshold_uncertainty_score":0.3991323,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01939596454917004,"score_gpt":0.2552481641668851,"score_spread":0.235852199617715,"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."}}