{"id":"W4393726878","doi":"10.5281/zenodo.1322046","title":"Ibm (Meganyctiphanes Norvegica And Thysanoessa Raschii) -- Datasets","year":2018,"lang":"en","type":"dataset","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Digital Imaging for Blood Diseases","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"","keywords":"IBM; Physics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0005032534,0.0003845693,0.0003208592,0.000435254,0.001839749,0.006064993,0.004860334,0.0001289586,0.002074213],"category_scores_gemma":[0.0008432723,0.0003930536,0.00007807167,0.0006666391,0.0004954369,0.001519921,0.007812276,0.0003719048,0.009280491],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007715997,"about_ca_system_score_gemma":0.00001405138,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003899268,"about_ca_topic_score_gemma":0.00000116846,"domain_scores_codex":[0.9969161,0.0003090177,0.0003535452,0.001122869,0.0007042646,0.0005942545],"domain_scores_gemma":[0.9968727,0.00005159155,0.0002380848,0.001971421,0.0004211934,0.0004450619],"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":[0.00001613106,0.0001974969,2.662013e-7,0.0001430519,0.00005895428,0.00006792245,0.00005048549,8.465167e-7,0.00002429444,0.0004569991,0.9829224,0.01606109],"study_design_scores_gemma":[0.000390445,0.0002259322,0.00005311046,0.00008518223,0.0000414628,0.0003100898,0.00001323994,0.00009527792,0.00005270382,0.0003233812,0.9979807,0.0004284736],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00007373567,0.0002762864,0.0007746794,0.0004810621,0.0002842554,0.0004174558,0.9905792,0.001016469,0.006096866],"genre_scores_gemma":[0.0004160531,0.0002140944,0.0005847845,0.0004549228,0.0002778906,8.084474e-8,0.9971418,0.000745027,0.0001653833],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.01563262,"threshold_uncertainty_score":0.9998521,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02349614396625031,"score_gpt":0.2473753183913796,"score_spread":0.2238791744251293,"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."}}