{"id":"W2143804471","doi":"10.5539/mas.v6n4p77","title":"Partial Erosion-Based Feature Extraction Approach for Plastic Bottle Shape Classification","year":2012,"lang":"en","type":"article","venue":"Modern Applied Science","topic":"Industrial Vision Systems and Defect Detection","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Structuring element; Silhouette; Erosion; Artificial intelligence; Histogram; Computer science; Pixel; Pattern recognition (psychology); Normalization (sociology); Plastic bottle; Feature (linguistics); Mathematical morphology; Bin; Image processing; Computer vision; Bottle; Image (mathematics); Algorithm; Geology; Materials science","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":[],"consensus_categories":[],"category_scores_codex":[0.0005972011,0.0001249372,0.0001158432,0.0001235064,0.0003096048,0.00009368236,0.0001301226,0.0001424876,0.000009222394],"category_scores_gemma":[0.00004560662,0.0001125892,0.00004070327,0.0003570803,0.00006299119,0.0002628303,0.00001017017,0.0001561692,0.00002748102],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001481016,"about_ca_system_score_gemma":0.00003930186,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002145839,"about_ca_topic_score_gemma":3.911325e-7,"domain_scores_codex":[0.9988852,0.000008565351,0.0001584403,0.0002440219,0.0003333749,0.0003703751],"domain_scores_gemma":[0.9995,0.00007850392,0.00005163202,0.0001986779,0.00004475564,0.0001264259],"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":[0.00003338372,0.00003257581,0.00006638195,0.00002432515,0.000001930696,2.302873e-8,0.0001005453,0.02915378,0.9586537,0.0003371777,0.0004599053,0.0111362],"study_design_scores_gemma":[0.0002803096,0.00001598464,0.001353006,0.000005398807,0.000007901755,0.000001510806,0.00004987297,0.9336241,0.06308138,0.00002322928,0.00142217,0.0001351509],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06806365,0.00002893586,0.9280884,0.000008388045,0.001063106,0.0004614703,0.000006811867,0.0002357237,0.002043465],"genre_scores_gemma":[0.9956513,5.159239e-7,0.003551725,0.0000140757,0.0004702233,0.0002471209,0.00001212541,0.00002026429,0.00003262906],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9275877,"threshold_uncertainty_score":0.4591253,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04543082391590787,"score_gpt":0.2667462710721465,"score_spread":0.2213154471562387,"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."}}