{"id":"W4398699092","doi":"10.7910/dvn/j3ihly","title":"Discovery-IHNV","year":2015,"lang":"en","type":"dataset","venue":"Harvard Dataverse","topic":"Medical Imaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"North Pacific Marine Science Organization","funders":"","keywords":"Computational biology; Computer science; Biology","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":[0.001680948,0.002315938,0.002118108,0.004237792,0.001404929,0.002502517,0.004342663,0.00296048,0.1096686],"category_scores_gemma":[0.008830269,0.0009833669,0.002380253,0.005488663,0.0008878975,0.0008968128,0.002278668,0.002113633,0.05657202],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003168972,"about_ca_system_score_gemma":0.007624305,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1506654,"about_ca_topic_score_gemma":0.2597952,"domain_scores_codex":[0.9988977,0.0001811952,0.000122366,0.0002892355,0.0002957344,0.0002137129],"domain_scores_gemma":[0.9969644,0.001139442,0.000246982,0.0005870906,0.0006555833,0.0004065459],"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":[0.0001062578,0.00002966585,0.00123369,0.0009878903,0.0000745884,0.00003718122,0.00003571604,0.0007696776,0.0001512913,0.000474542,0.9943211,0.001778378],"study_design_scores_gemma":[0.001061236,0.00004164789,0.007412908,0.0006849144,0.0001566083,0.00015869,0.0001406331,0.001541635,0.0007585491,0.002408399,0.985558,0.00007671858],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001206922,0.00006583929,0.00004681349,0.00005838492,0.00002519971,0.00001176554,0.9991309,0.000297491,0.0002430194],"genre_scores_gemma":[0.0006144356,0.00007852832,0.0002633847,0.00006343159,0.000009117201,0.00007108245,0.9982916,0.00009287934,0.0005155347],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1506654,"threshold_uncertainty_score":0.3668779,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03368628326717386,"score_gpt":0.3202818149910741,"score_spread":0.2865955317239002,"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."}}