{"id":"W7062146424","doi":"","title":"Slimgim-T: GIS Capability Maturity Model For State Departments of Transportation","year":2018,"lang":"en","type":"other","venue":"Rosa P: A digital library for transportation research (United States Department of Transportation)","topic":"Thermal Analysis in Power Transmission","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Federal Highway Administration; Utah Department of Transportation; U.S. Department of Transportation","keywords":"Geospatial analysis; Capability Maturity Model; Maturity (psychological); State (computer science); Geographic information system; Information system; Center (category theory)","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"],"consensus_categories":[],"category_scores_codex":[0.0003584631,0.0008313564,0.001149279,0.001378694,0.0001470379,0.0001071046,0.0006698587,0.0005023262,0.0006670165],"category_scores_gemma":[0.00001184176,0.0008593131,0.0008334863,0.001417094,0.0004749866,0.001278996,0.000003207294,0.0003489981,0.00001507054],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007798284,"about_ca_system_score_gemma":0.0001998698,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002128236,"about_ca_topic_score_gemma":0.0007394496,"domain_scores_codex":[0.9948307,0.0000690224,0.001967001,0.0008938103,0.001318416,0.0009209983],"domain_scores_gemma":[0.9974257,0.0003901809,0.0005700249,0.000650709,0.0005635745,0.0003997703],"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":[0.00536572,0.002744014,0.003046334,0.02848753,0.004161576,0.00003024526,0.004682584,0.0772182,0.0001945561,0.002466737,0.8681272,0.003475279],"study_design_scores_gemma":[0.003981169,0.0008602306,0.001465162,0.0007836348,0.0006107406,2.45074e-7,0.0002560864,0.05524323,0.00885968,0.006971746,0.919787,0.001181025],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0384357,0.0002206879,0.09107231,0.00007620198,0.0001807383,0.01353634,0.8551481,0.0007809475,0.0005490006],"genre_scores_gemma":[0.1108068,0.0004649592,0.01361908,0.00002570787,0.00007203319,0.007352029,0.8527558,0.001123854,0.01377974],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.07745323,"threshold_uncertainty_score":0.9993858,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02334953123601,"score_gpt":0.2764120997519287,"score_spread":0.2530625685159186,"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."}}