{"id":"W6911607853","doi":"10.5281/zenodo.13348408","title":"Ready Mix Concrete","year":2024,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Innovations in Concrete and Construction Materials","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Order (exchange); Building industry; Service (business); Focus (optics); Construction industry","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0009269296,0.002360614,0.0009640157,0.003730733,0.002183006,0.003332584,0.002876994,0.002379782,0.472187],"category_scores_gemma":[0.003274697,0.00163449,0.001030826,0.001485983,0.0008441387,0.003996025,0.004688193,0.002718275,0.29987],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001385673,"about_ca_system_score_gemma":0.002244509,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004685357,"about_ca_topic_score_gemma":0.01136552,"domain_scores_codex":[0.9972474,0.0001102614,0.000128953,0.0004002249,0.001881626,0.0002314295],"domain_scores_gemma":[0.9978746,0.000181816,0.0001370119,0.0003587187,0.001081909,0.0003659658],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.0003510029,0.0004732381,0.002024647,0.001850743,0.00004296636,0.0009151233,0.0006692063,0.005093445,0.06467748,0.03003523,0.5212364,0.3726304],"study_design_scores_gemma":[0.00002704738,0.0000655529,0.0009515482,0.0001698245,0.00002138616,0.0004145767,0.0002034385,0.001311632,0.01799271,0.002084999,0.9766891,0.00006815371],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.01106013,0.001264294,0.06105101,0.000992511,0.001947693,0.001125462,0.009349845,0.03356574,0.8796433],"genre_scores_gemma":[0.05440377,0.000901796,0.04150707,0.001171245,0.0001807014,0.0005477724,0.006467818,0.01089476,0.8839251],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.472187,"threshold_uncertainty_score":0.7528611,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02656275473214372,"score_gpt":0.2351885410489921,"score_spread":0.2086257863168484,"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."}}