{"id":"W4405733893","doi":"10.18280/i2m.230604","title":"Enhancing Ship Coating Quality Detection via Machine Learning-Optimized Visible Near-Infrared Spectroscopy","year":2024,"lang":"en","type":"article","venue":"Instrumentation Mesure Métrologie","topic":"Spectroscopy and Chemometric Analyses","field":"Chemistry","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Kementerian Pendidikan, Kebudayaan, Riset, dan Teknologi","keywords":"Infrared; Coating; Spectroscopy; Infrared spectroscopy; Quality (philosophy); Materials science; Computer science; Optics; Chemistry; Nanotechnology; Physics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.000854252,0.0003575466,0.0004636748,0.0002393198,0.0004464459,0.000431777,0.0002416786,0.0002758417,0.003259184],"category_scores_gemma":[0.0005935756,0.0003461183,0.0002395318,0.0009691305,0.0001090216,0.0004129439,0.00007292353,0.0008321197,0.0001421718],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004387973,"about_ca_system_score_gemma":0.0001200113,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003097157,"about_ca_topic_score_gemma":0.00007833965,"domain_scores_codex":[0.9973968,0.0001771028,0.0007347187,0.000680371,0.0004762544,0.0005347571],"domain_scores_gemma":[0.9986914,0.0005208835,0.0002743647,0.0003149891,0.00008129323,0.0001171131],"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":[0.000224972,0.00005332739,0.01453526,0.0002317212,0.0002489587,0.00001502499,0.0003525885,0.0005384244,0.9783349,0.00006159273,0.00005410834,0.005349108],"study_design_scores_gemma":[0.0009674678,0.000130742,0.001200147,0.00003392529,0.0002349221,0.00001819552,0.0004695104,0.01555575,0.9792098,0.001206326,0.0006186032,0.0003545437],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8804922,0.001204461,0.1085335,0.0003291524,0.0004024076,0.0001420714,0.00002610828,0.001275791,0.007594342],"genre_scores_gemma":[0.9865706,0.0001134264,0.01111664,0.0001365727,0.0002315441,0.00005607753,0.0001788384,0.00005209028,0.001544209],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1060785,"threshold_uncertainty_score":0.9998991,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02712663506976446,"score_gpt":0.3331259743461424,"score_spread":0.3059993392763779,"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."}}