{"id":"W6931320001","doi":"10.5281/zenodo.5943303","title":"PowerGenome/PowerGenome: v0.5.2","year":2022,"lang":"en","type":"other","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Advanced Technology in Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Impact","funders":"","keywords":"Test (biology); Nuclear power; Table (database); Test data; Nuclear data","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":[0.001767139,0.003186901,0.001425886,0.001941057,0.001421771,0.003560095,0.005209395,0.002433957,0.3166163],"category_scores_gemma":[0.007920582,0.003319901,0.002374975,0.001986851,0.000677445,0.004694712,0.004490569,0.00411054,0.4167609],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00124669,"about_ca_system_score_gemma":0.001249243,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006088876,"about_ca_topic_score_gemma":0.006382056,"domain_scores_codex":[0.9987307,0.0001490405,0.00007768261,0.000318663,0.0005341908,0.0001896993],"domain_scores_gemma":[0.9977971,0.0004886832,0.0000992916,0.000832496,0.0005947584,0.000187682],"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":[0.0002259437,0.00004036894,0.0006448121,0.0005325116,0.00004873298,0.00006932458,0.000125406,0.0004958931,0.002859372,0.001483569,0.9688145,0.02465952],"study_design_scores_gemma":[0.0001529461,0.00003494771,0.0008835179,0.0001160047,0.00004004826,0.0001545846,0.00004331141,0.001247276,0.01035482,0.003455965,0.9834211,0.00009553156],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"software","genre_gemma":"software","genre_scores_codex":[0.0009004687,0.0004014022,0.0344338,0.0005321079,0.0004887994,0.0001693234,0.1166275,0.8155597,0.03088686],"genre_scores_gemma":[0.00641764,0.000308877,0.02150911,0.001146963,0.00009074977,0.0004273619,0.2381376,0.705739,0.02622283],"genre_candidate":"software","genre_consensus":"software","teacher_disagreement_score":0.3166163,"threshold_uncertainty_score":0.9747639,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01937899990115359,"score_gpt":0.2421928932069866,"score_spread":0.222813893305833,"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."}}