{"id":"W4393629559","doi":"10.5281/zenodo.1068363","title":"Bio2Vec","year":2017,"lang":"en","type":"dataset","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Cell Image Analysis Techniques","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science","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":"codex-gemma-dda1882f352a","candidate_categories":["sts","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0004772563,0.0002248835,0.0002057095,0.0001915851,0.001637445,0.0009065958,0.00229919,0.0002657232,0.005982897],"category_scores_gemma":[0.0008676355,0.0002430238,0.00013311,0.0001127835,0.0002313549,0.0000105232,0.002734067,0.0003047074,0.007324743],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004632682,"about_ca_system_score_gemma":0.000006291897,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004413105,"about_ca_topic_score_gemma":0.000002501615,"domain_scores_codex":[0.9983743,0.0001992949,0.0002238419,0.0006278871,0.000263923,0.0003107347],"domain_scores_gemma":[0.997315,0.000003716327,0.0002345061,0.001862103,0.0004525269,0.0001320925],"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":[0.00002178538,0.00006872304,1.185991e-7,0.00004630271,0.00008744885,0.00001295577,0.000006479568,6.000524e-7,0.01403121,0.000004483578,0.9759961,0.009723826],"study_design_scores_gemma":[0.0001596635,0.0001957151,0.000009534097,0.00002348225,0.00005325297,0.00006479661,0.000008673645,0.00000299806,0.005527815,0.00001482259,0.9936782,0.0002610247],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001414111,0.0003166343,0.0005238847,0.0001405102,0.00006200748,0.0003870798,0.9693662,0.000255963,0.02880631],"genre_scores_gemma":[0.0007408714,0.001043055,0.00008573841,0.0001421725,0.0004013572,4.763283e-8,0.9945756,0.0009377581,0.002073454],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.02673285,"threshold_uncertainty_score":0.9996623,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02161729349972346,"score_gpt":0.2853365006521172,"score_spread":0.2637192071523937,"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."}}