{"id":"W2021698410","doi":"10.1007/bf02480874","title":"Appendix BELCAM Roofing Data Collection Protocol and integration with predictive tools","year":2003,"lang":"en","type":"article","venue":"Materials and Structures","topic":"Industrial Automation and Control Systems","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Public Works and Government Services Canada","funders":"","keywords":"Solid mechanics; Protocol (science); Data collection; Engineering; Computer science; Mathematics; Statistics; Materials science; Medicine; Composite material; Pathology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001286287,0.000100243,0.0001379299,0.00003263683,0.00009418696,0.000244795,0.00004007469,0.00005549748,0.00007924193],"category_scores_gemma":[0.00002615509,0.00007023122,0.000003287853,0.00004464516,0.00001641385,0.0002172583,0.00001144233,0.0000412297,0.000001106959],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001395786,"about_ca_system_score_gemma":0.0000109295,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004186894,"about_ca_topic_score_gemma":0.00003170128,"domain_scores_codex":[0.9995102,0.00005091955,0.0001499494,0.0001295252,0.00007024901,0.00008920015],"domain_scores_gemma":[0.9997932,0.0000134873,0.00003757726,0.0001124329,0.00001675407,0.00002655542],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001408674,0.0000366388,0.00122067,0.0009248631,0.0003985455,0.00001216576,0.002361454,0.002893312,0.8894164,0.03534901,0.007839492,0.05813877],"study_design_scores_gemma":[0.01521312,0.00189877,0.05288841,0.0006270199,0.0002042041,0.0004849626,0.001655531,0.06437406,0.7956854,0.007037379,0.05816988,0.00176128],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9509953,0.00004381595,0.01090291,0.00003475662,0.0006862874,0.03303965,0.000207522,0.0003469521,0.003742825],"genre_scores_gemma":[0.9965777,0.000001857071,0.0003421967,0.000008402609,0.00008767749,0.00288822,0.00005327226,0.00001109907,0.0000295982],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.09373103,"threshold_uncertainty_score":0.2863946,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0193811589616463,"score_gpt":0.2333811954815527,"score_spread":0.2140000365199064,"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."}}