{"id":"W576640945","doi":"","title":"What Do I Have and Where is it Located? Quantifying Ontario’s Municipal Lane Kilometres","year":2014,"lang":"fr","type":"article","venue":"Transportation 2014: Past, Present, Future - 2014 Conference and Exhibition of the Transportation Association of Canada // Transport 2014 : Du passé vers l'avenir - 2014 Congrès et Exposition de 'Association des transports du Canada","topic":"Infrastructure Maintenance and Monitoring","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Business; Kilometer; Asset (computer security); Context (archaeology); Asset management; Data collection; Transport engineering; Finance; Environmental resource management; Geography; Computer science; Economics; Engineering","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":[0.001739663,0.001086252,0.001468763,0.000316008,0.0006722377,0.0002389842,0.0004965249,0.0009971142,0.001641286],"category_scores_gemma":[0.00003931931,0.001171953,0.0004838558,0.0003824437,0.0002885352,0.002180687,0.000007902081,0.001113812,0.000003803769],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003327373,"about_ca_system_score_gemma":0.003123623,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8910599,"about_ca_topic_score_gemma":0.9969518,"domain_scores_codex":[0.9924101,0.0005006558,0.002486915,0.001002955,0.002284775,0.001314576],"domain_scores_gemma":[0.9937016,0.0005313033,0.002512126,0.0006031962,0.002015022,0.0006367662],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003998672,0.0001743926,0.7897713,0.002184084,0.001191887,0.00004846898,0.02769019,0.02150168,0.001034845,0.004609712,0.1499569,0.001436698],"study_design_scores_gemma":[0.003856656,0.0001911435,0.7825856,0.001647292,0.001645321,0.00001235073,0.006629827,0.001008125,0.003384502,0.0006107698,0.1970816,0.001346734],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9406377,0.003383436,0.008359675,0.03333636,0.007002039,0.00160713,0.004756105,0.0001276187,0.0007899136],"genre_scores_gemma":[0.9752988,0.01794694,0.000546566,0.0008008872,0.000742966,0.00009369368,0.002136116,0.0001333122,0.002300696],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1058918,"threshold_uncertainty_score":0.9992713,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0089019806074352,"score_gpt":0.2108945616517796,"score_spread":0.2019925810443444,"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."}}