{"id":"W4386188647","doi":"10.2139/ssrn.4548759","title":"Defect Detection in Pharmaceutical Vials Using Computer Vision System","year":2023,"lang":"en","type":"preprint","venue":"SSRN Electronic Journal","topic":"Advanced Statistical Process Monitoring","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Horizon College and Seminary","funders":"","keywords":"Vial; Computer vision; Computer science; Artificial intelligence; Process engineering; Chromatography; Chemistry; Engineering","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004220478,0.0003447446,0.0006190254,0.00127236,0.0002081959,0.0006308489,0.0005464749,0.0009583635,0.001059977],"category_scores_gemma":[0.001042838,0.0002384576,0.000467333,0.0006549197,0.0002034559,0.0005334927,0.0003211933,0.0003302607,0.0003420257],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004137348,"about_ca_system_score_gemma":0.0003567896,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001832426,"about_ca_topic_score_gemma":0.001257905,"domain_scores_codex":[0.9995458,0.00004412328,0.00002279474,0.0001078469,0.0002303694,0.00004914447],"domain_scores_gemma":[0.9990941,0.0002537677,0.0001554076,0.00007800254,0.0003799153,0.00003879351],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001950154,0.0004511901,0.02815805,0.0004443285,0.0001237019,0.0006343436,0.0001684203,0.03658237,0.4785801,0.0006406311,0.002448272,0.4498183],"study_design_scores_gemma":[0.00003077037,0.0006396571,0.02820314,0.00001916053,0.00008169374,0.000488901,0.0000672751,0.8264239,0.1427471,0.0004285161,0.0008261941,0.00004373264],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7803546,0.001294895,0.2139454,0.0001435664,0.0001029873,0.00009266231,0.0003333541,0.001970226,0.001762301],"genre_scores_gemma":[0.9550252,0.0002301396,0.04337042,0.00004223075,0.00002247929,0.00002175551,0.0001703809,0.00004153037,0.00107595],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001832426,"threshold_uncertainty_score":0.003643513,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1598160647322673,"score_gpt":0.478734726355055,"score_spread":0.3189186616227878,"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."}}