{"id":"W7036528418","doi":"","title":"Caso de aproximación a trombocitopenia inmunomediada (TIM)","year":2022,"lang":"es","type":"report","venue":"LA Referencia (Red Federada de Repositorios Institucionales de Publicaciones Científicas)","topic":"Medical Image Segmentation Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Research methodology; Population; Context (archaeology)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002924557,0.0004978281,0.000419281,0.001366785,0.0007102262,0.0008120411,0.000409014,0.001319325,0.003692695],"category_scores_gemma":[0.001542531,0.0003158374,0.0004062772,0.000945135,0.0006570986,0.0005508891,0.000427576,0.001071038,0.0006758593],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001088309,"about_ca_system_score_gemma":0.0008192147,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01154209,"about_ca_topic_score_gemma":0.02121895,"domain_scores_codex":[0.9997287,0.00002240982,0.00002165515,0.00003890161,0.00006330949,0.0001249931],"domain_scores_gemma":[0.9992973,0.0002175085,0.0002380653,0.0000475524,0.00008042176,0.000119242],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"case_report","study_design_gemma":"case_report","study_design_scores_codex":[0.0004211229,0.0001744039,0.06931443,0.0001850697,0.00003968475,0.8979849,0.0008889387,0.0001426214,0.009649279,0.0005876521,0.002274256,0.01833762],"study_design_scores_gemma":[0.00004932631,0.0006731941,0.08268557,0.0001087347,0.0001461033,0.8873482,0.0009579443,0.0009999889,0.0109661,0.0003489026,0.01568852,0.00002741161],"study_design_candidate":"case_report","study_design_consensus":"case_report","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9462792,0.004859455,0.004781836,0.003072149,0.0002793598,0.0003345947,0.0004315334,0.0002807711,0.03968113],"genre_scores_gemma":[0.9879561,0.001852,0.001621555,0.001050059,0.0002088334,0.00003129731,0.0001872015,0.00002597555,0.007067013],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01154209,"threshold_uncertainty_score":0.02294981,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03093085361410786,"score_gpt":0.2834536563255615,"score_spread":0.2525228027114537,"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."}}