{"id":"W6968119745","doi":"10.5281/zenodo.1292784","title":"research-iobserve/jpetstore-6: Single Archive JPetStore with iObserve instrumentation","year":2018,"lang":"en","type":"other","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Machine Learning in Bioinformatics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Apache (Canada)","funders":"","keywords":"Instrumentation (computer programming); Data acquisition; Key (lock); Component (thermodynamics)","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":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0008472256,0.0003480891,0.0002511217,0.0004539503,0.001207279,0.0005556874,0.001414704,0.0003048735,0.01260229],"category_scores_gemma":[0.000544961,0.0003365507,0.00007863875,0.0004610988,0.000696755,0.00002040251,0.001606883,0.000557206,0.006566428],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001444312,"about_ca_system_score_gemma":0.00002123789,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007793288,"about_ca_topic_score_gemma":0.00002298362,"domain_scores_codex":[0.99694,0.0006591058,0.0003327417,0.0006992048,0.0007477545,0.0006212549],"domain_scores_gemma":[0.9977773,0.00001676911,0.0003244898,0.001031978,0.0006082589,0.0002411899],"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":[0.0001717188,0.0001343848,0.00001791379,0.0002216266,0.0001449968,0.00000918353,0.0003879019,0.00002092729,0.005386939,0.0004546781,0.9822109,0.01083882],"study_design_scores_gemma":[0.0006888477,0.001676083,0.0001447195,0.0001956815,0.00002423965,0.00009607337,0.0003104732,0.00010149,0.001137178,0.0000372501,0.9952041,0.0003838453],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.005231954,0.0001634,0.003912743,0.0002150119,0.0001931585,0.0009836948,0.0005806015,0.0005898342,0.9881296],"genre_scores_gemma":[0.07659104,0.0008724054,0.02541449,0.0007278283,0.005112766,0.000002156263,0.09927455,0.03554101,0.7564638],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.2316658,"threshold_uncertainty_score":0.9999086,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02723348627373085,"score_gpt":0.2600930621648237,"score_spread":0.2328595758910929,"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."}}