{"id":"W4393792900","doi":"10.5281/zenodo.7693279","title":"Iterative Bleaching Extends Multiplexity (IBEX) Knowledge-Base","year":2023,"lang":"en","type":"dataset","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Industrial Vision Systems and Defect Detection","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Base (topology); Knowledge base; Computer science; Psychology; Artificial intelligence; Mathematics","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","sts","scholarly_communication","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.001191527,0.0003618679,0.0003727459,0.0006801615,0.001939307,0.00112535,0.0008571976,0.000368539,0.002952313],"category_scores_gemma":[0.0008444294,0.0003836939,0.0001368709,0.0009116033,0.00008139579,0.0002276735,0.0007729684,0.001144253,0.06514969],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000431162,"about_ca_system_score_gemma":0.000006232678,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001250425,"about_ca_topic_score_gemma":0.000006619455,"domain_scores_codex":[0.9974853,0.0005184739,0.0004918426,0.0005443064,0.0004169664,0.0005430662],"domain_scores_gemma":[0.9984159,0.00007538488,0.0001274016,0.0007227773,0.0004181178,0.0002403951],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00002581246,0.00004608047,3.458847e-8,0.0002393079,0.00007950688,0.00002785643,0.0002690497,0.000628557,0.0003430466,0.00002499749,0.9745646,0.02375113],"study_design_scores_gemma":[0.0004960051,0.0001511949,0.00001171313,0.0001969048,0.00002925691,0.00005926174,0.0001371677,0.001903265,0.0001686695,0.00001546301,0.9964495,0.0003815887],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0003596656,0.0001693667,0.00134056,0.00002901023,0.001844735,0.0007323278,0.9820207,0.003445014,0.01005864],"genre_scores_gemma":[0.003932282,0.0001417456,0.00003007868,0.00001817757,0.001163969,2.497973e-7,0.9914314,0.00235244,0.0009297205],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.06219738,"threshold_uncertainty_score":0.9999116,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06097144975372208,"score_gpt":0.2740905724267024,"score_spread":0.2131191226729803,"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."}}