{"id":"W3190574556","doi":"10.1007/s10694-021-01161-7","title":"Comparison of Techniques for Prediction of Mechanical Strength of Firefighters’ Protective Clothing Using Near-Infrared Spectral Data","year":2021,"lang":"en","type":"article","venue":"Fire Technology","topic":"Textile materials and evaluations","field":"Materials Science","cited_by":4,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta; University of Saskatchewan","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Clothing; Nondestructive testing; Absorbance; Materials science; Near-infrared spectroscopy; Hue; Environmental science; Composite material; Computer science; Optics; Artificial intelligence; Physics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0003926784,0.00010354,0.0004525334,0.00008234975,0.00007782253,0.00001296346,0.0003951672,0.0002328269,0.0001565774],"category_scores_gemma":[0.0005179127,0.0001006499,0.00004451297,0.0002654967,0.0002024926,0.000140694,0.0003199399,0.00008770019,8.146363e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000376184,"about_ca_system_score_gemma":0.0001679656,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000658471,"about_ca_topic_score_gemma":0.00001967961,"domain_scores_codex":[0.9986749,0.00006395829,0.0006064867,0.0003120497,0.000169137,0.0001734234],"domain_scores_gemma":[0.9985443,0.00007128875,0.0004465579,0.000668388,0.0002521238,0.00001731472],"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":[0.00004408873,0.0001558053,0.0003053324,0.0001391614,0.00001826668,5.315977e-7,0.0002142437,0.00002269018,0.9945109,0.001589824,0.0001093216,0.002889783],"study_design_scores_gemma":[0.0002400837,0.0003088951,0.0003770276,0.0001445685,0.00005719376,0.000007057972,0.0002946595,0.02899061,0.9633945,0.00593071,0.0001859959,0.00006869218],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9774961,0.00009307777,0.01961646,0.0001392193,0.0002043213,0.000513766,0.00174864,0.0001602853,0.00002813091],"genre_scores_gemma":[0.8773746,0.000003854423,0.1224416,0.000002625467,0.00002804728,0.00003736496,0.00009529682,0.00001212952,0.000004405911],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1028251,"threshold_uncertainty_score":0.4104382,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09943395774358638,"score_gpt":0.3644974460209306,"score_spread":0.2650634882773442,"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."}}