{"id":"W6889008152","doi":"10.25384/sage.21993096","title":"sj-jpg-2-wso-10.1177_17474930231152124 – Supplemental material for Characterizing mixed location hemorrhages/microbleeds with CSF markers","year":2023,"lang":"en","type":"other","venue":"Sage Journals Data","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Jewish General Hospital","funders":"","keywords":"Stroke (engine); Biopower; MEDLINE; Perivascular space","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00217833,0.00147819,0.001598797,0.003306911,0.001511933,0.003824762,0.002880158,0.003916966,0.7225173],"category_scores_gemma":[0.007496597,0.001756902,0.00131482,0.002598177,0.0005839295,0.002549896,0.002222733,0.002850933,0.4959548],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001387298,"about_ca_system_score_gemma":0.002824405,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007330114,"about_ca_topic_score_gemma":0.01527588,"domain_scores_codex":[0.9985122,0.0001616095,0.0001955771,0.0002468194,0.0006538327,0.0002299079],"domain_scores_gemma":[0.9944022,0.001870821,0.000440436,0.0008246489,0.001414489,0.001047469],"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":[0.0004375604,0.0001587151,0.0007119008,0.0004181153,0.00002712955,0.0001127846,0.00003105345,0.00009269228,0.003465434,0.0006688665,0.981725,0.01215076],"study_design_scores_gemma":[0.0009369072,0.0002348663,0.00813471,0.0003885747,0.00005361655,0.0006288055,0.0001124763,0.0005055959,0.007809679,0.002195388,0.9789183,0.00008121261],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.001469445,0.0005310383,0.005628618,0.00188996,0.001334762,0.0006922513,0.9142936,0.01485211,0.05930838],"genre_scores_gemma":[0.006378094,0.0007609531,0.01182529,0.001998459,0.0005118477,0.001448493,0.9008892,0.01022825,0.06595937],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.7225173,"threshold_uncertainty_score":0.3957955,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03932939757520488,"score_gpt":0.3011547664506134,"score_spread":0.2618253688754085,"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."}}