{"id":"W4393708377","doi":"10.5281/zenodo.1322047","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; Optics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007497993,0.002366055,0.001243714,0.002552005,0.0007535341,0.001686526,0.003086891,0.001860912,0.03722683],"category_scores_gemma":[0.003154434,0.0005346745,0.001639271,0.003874586,0.0004455415,0.001018937,0.001581811,0.00183725,0.06075653],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001423471,"about_ca_system_score_gemma":0.001778442,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02165996,"about_ca_topic_score_gemma":0.04072436,"domain_scores_codex":[0.9993694,0.00008451355,0.00007282147,0.0002094609,0.0001512612,0.0001125296],"domain_scores_gemma":[0.9989877,0.0002377924,0.000105206,0.0002733108,0.0002767824,0.0001192814],"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":[0.0001335313,0.00005239472,0.001928375,0.001076557,0.00007048249,0.00004054643,0.00003698473,0.001113695,0.0003317524,0.0005366498,0.9904445,0.004234561],"study_design_scores_gemma":[0.0003663927,0.00003798422,0.009499956,0.0003327731,0.0000699122,0.0001168976,0.000114798,0.001792726,0.000686129,0.0014534,0.9854879,0.00004120004],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.000303137,0.00007324786,0.00006822225,0.00004168139,0.00002137042,0.00001137071,0.9985946,0.0004376873,0.0004486997],"genre_scores_gemma":[0.0003860491,0.00003663446,0.0002535122,0.00002044771,0.000003396288,0.00005292016,0.9988919,0.00003668666,0.0003185003],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.03722683,"threshold_uncertainty_score":0.1245362,"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."}}