{"id":"W158475136","doi":"","title":"Friction and Prediction","year":2007,"lang":"en","type":"article","venue":"International airport review","topic":"Smart Materials for Construction","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Runway; Snow; Frost (temperature); Environmental science; Engineering; Meteorology; Aeronautics; Marine engineering; Forensic engineering; Geography","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0004412485,0.00005817095,0.00006965367,0.00002147141,0.00003888538,0.00001140698,0.00006568977,0.00002400898,0.002022868],"category_scores_gemma":[0.00003652236,0.00005263391,0.00002534262,0.00006470673,0.00004454498,0.0002132126,0.00005600342,0.00003692676,0.0003500143],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009134638,"about_ca_system_score_gemma":0.000002262728,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008998015,"about_ca_topic_score_gemma":0.00004089721,"domain_scores_codex":[0.9993351,0.000008517583,0.0002178873,0.0001477181,0.0002146349,0.00007620843],"domain_scores_gemma":[0.9997789,0.000009725271,0.00008511337,0.00007535972,0.00001090756,0.00003995137],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000009756207,0.00002427641,0.8853555,0.00006410605,0.00001570601,0.000008013451,0.00001787885,0.000003646247,0.003127481,0.000701069,0.01185641,0.0988161],"study_design_scores_gemma":[0.00005968802,0.00001196828,0.5826764,0.0001374507,0.00001237547,0.0001621778,0.000002731852,0.00002719128,0.0003525004,0.00033234,0.4161732,0.00005191802],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9507113,0.001698612,0.002409977,0.001056898,0.002402626,0.0003170836,0.000008775152,0.0001022537,0.04129245],"genre_scores_gemma":[0.9879755,0.00889772,0.001452666,0.0009291663,0.0002738573,0.00001662736,0.00004167469,0.000009807833,0.000402954],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4043168,"threshold_uncertainty_score":0.9988894,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008568654807044974,"score_gpt":0.2462572790038415,"score_spread":0.2376886241967966,"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."}}