{"id":"W2611731774","doi":"10.1175/wcas-d-16-0103.1","title":"Planning for Winter Road Maintenance in the Context of Climate Change","year":2017,"lang":"en","type":"article","venue":"Weather Climate and Society","topic":"Smart Materials for Construction","field":"Environmental Science","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"Quest University Canada; University of Waterloo","funders":"","keywords":"Climate change; Context (archaeology); Snow; Environmental science; Percentile; Baseline (sea); Climatology; Precipitation; Meteorology; Geography; Political science; Mathematics; Statistics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0005886952,0.0002669852,0.0002335517,0.0006407428,0.0006789439,0.00121328,0.0006086798,0.0003122572,0.00125896],"category_scores_gemma":[0.001393867,0.0001648369,0.0002476372,0.0009237274,0.0002755154,0.0004815244,0.000481389,0.0004266272,0.00008128444],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004261756,"about_ca_system_score_gemma":0.004451472,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.3489492,"about_ca_topic_score_gemma":0.5553656,"domain_scores_codex":[0.9996301,0.000138063,0.00001182704,0.00004570402,0.00006441005,0.0001097984],"domain_scores_gemma":[0.9994518,0.0001269917,0.0001114419,0.00002695041,0.0001500629,0.0001327556],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.0001144168,0.0001179057,0.2887726,0.00006980101,0.0001146019,0.0004692703,0.0005181357,0.6683788,0.00205874,0.002703406,0.003537976,0.03314444],"study_design_scores_gemma":[0.00001593332,0.0001129958,0.2157239,0.0000317406,0.00005046407,0.00007320035,0.00508561,0.7704619,0.001139097,0.003280475,0.003994047,0.00003073641],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9835881,0.0001115425,0.01001546,0.0004874344,0.00001093246,0.00006076346,0.0008099092,0.0001072544,0.004808663],"genre_scores_gemma":[0.9965274,0.00005220903,0.002734509,0.000008710929,0.000002970326,0.00001320317,0.0003107018,0.000004953767,0.0003453053],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3489492,"threshold_uncertainty_score":0.6938361,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02903813878784033,"score_gpt":0.2711470978435785,"score_spread":0.2421089590557382,"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."}}