{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0005365804,0.0004826593,0.000468439,0.0003311778,0.0001549413,0.00003944261,0.0004772398,0.0004545705,0.003807597],"category_scores_gemma":[0.00008756873,0.0006392823,0.0002413455,0.0002630191,0.0000383279,0.0001548913,0.001242818,0.002028482,0.002370751],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008017066,"about_ca_system_score_gemma":0.00006261297,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001967325,"about_ca_topic_score_gemma":0.00006327546,"domain_scores_codex":[0.9974397,0.0001508951,0.0005604718,0.0008595762,0.0004844134,0.0005049423],"domain_scores_gemma":[0.9983606,0.00006170187,0.0001548124,0.001154088,0.000101759,0.0001670038],"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":[0.000195404,0.0003057403,0.1090243,0.002841071,0.001214032,0.0001679371,0.002974763,0.3477509,0.4779326,0.00005291461,0.0001913914,0.05734899],"study_design_scores_gemma":[0.000970902,0.0000412355,0.1996386,0.0002958087,0.0002792609,0.00006488558,0.0002799341,0.06837817,0.702047,0.001624918,0.02446512,0.001914197],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9773767,0.000184508,0.000582824,0.0000483613,0.002720555,0.0007731195,0.00008618552,0.001899561,0.0163282],"genre_scores_gemma":[0.9977579,0.0004294798,0.0001805318,0.00003157945,0.0003358583,0.0004783385,0.0002484928,0.0001710215,0.0003667836],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2793727,"threshold_uncertainty_score":0.9996058,"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."}}