{"id":"W4220941786","doi":"10.20944/preprints202203.0172.v1","title":"SCD: Stacked Carton Scene Detection","year":2022,"lang":"en","type":"preprint","venue":"Preprints.org","topic":"Vehicle License Plate Recognition","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Carton; Computer science; Artificial intelligence; Classifier (UML); Computer vision; 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":[0.0004066559,0.002790357,0.00136349,0.002749307,0.0007052046,0.001513774,0.002527084,0.001399689,0.006670192],"category_scores_gemma":[0.0008705556,0.0006806238,0.001293934,0.001810643,0.0004435581,0.001376877,0.001809247,0.001197842,0.004680052],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001203027,"about_ca_system_score_gemma":0.001646295,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02739462,"about_ca_topic_score_gemma":0.07388615,"domain_scores_codex":[0.9991226,0.00004962371,0.00002174256,0.0003249796,0.0002412994,0.0002396985],"domain_scores_gemma":[0.9995912,0.00003968873,0.00003262767,0.0001370656,0.0001519802,0.00004750052],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0009860066,0.000542025,0.01348034,0.0006700438,0.0004007567,0.0008188654,0.0001314593,0.0315496,0.04533996,0.00313067,0.3613354,0.5416148],"study_design_scores_gemma":[0.0001528643,0.0003758864,0.02126697,0.00015422,0.0001876843,0.002000433,0.0003506588,0.7688956,0.07824714,0.006352699,0.1218483,0.0001676185],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3115275,0.00636436,0.345515,0.001327105,0.00191154,0.001588003,0.1114838,0.1776757,0.04260712],"genre_scores_gemma":[0.4140536,0.001222587,0.3167989,0.001108022,0.0002076548,0.0004261344,0.2448925,0.003019485,0.01827123],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02739462,"threshold_uncertainty_score":0.05447036,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08687413602871742,"score_gpt":0.3008521564477892,"score_spread":0.2139780204190718,"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."}}