{"id":"W2568280260","doi":"","title":"TRA-935: REPAIRING HIGH VOLUME HMA HIGHWAYS WITH PRECAST CONCRETE INLAY PANELS","year":2016,"lang":"en","type":"article","venue":"Scholarship@Western (Western University)","topic":"Material Properties and Applications","field":"Materials Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Precast concrete; Inlay; Structural engineering; Engineering; Geotechnical engineering; Materials science; Composite material","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000475222,0.0006348526,0.000234285,0.001022784,0.0008203491,0.001020518,0.001385367,0.0008768594,0.01209232],"category_scores_gemma":[0.000503476,0.0003301464,0.0004777286,0.0004174111,0.0004598671,0.0005228701,0.0006830944,0.0005792698,0.002386441],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001139773,"about_ca_system_score_gemma":0.003090722,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.07750702,"about_ca_topic_score_gemma":0.2488111,"domain_scores_codex":[0.9995824,0.00002117564,0.00001670597,0.00005096721,0.0002202131,0.0001086658],"domain_scores_gemma":[0.9996523,0.00002456678,0.00004112353,0.00005153714,0.0001427721,0.00008779715],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001424955,0.001817131,0.02307444,0.000946586,0.0002020298,0.004398651,0.001063977,0.09504688,0.3051276,0.002429006,0.04151232,0.5229565],"study_design_scores_gemma":[0.0005234948,0.0109103,0.1917321,0.0003710627,0.0004933073,0.01299958,0.004887922,0.2316762,0.3608906,0.001538588,0.1837226,0.0002542852],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8887491,0.000835685,0.04137413,0.0002855993,0.0002416146,0.0008519127,0.00139453,0.003125886,0.06314152],"genre_scores_gemma":[0.8974875,0.0003776913,0.03451316,0.00007438211,0.0000218447,0.00007445563,0.001380383,0.0001664482,0.06590414],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07750702,"threshold_uncertainty_score":0.1541117,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07161347493387082,"score_gpt":0.2644260774951305,"score_spread":0.1928126025612597,"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."}}