{"id":"W6946459488","doi":"10.34943/d9e96ae3-679c-47a0-8c7f-4b54d58103d2","title":"China Creek Power Supply Deployed 2019-11-04","year":2019,"lang":"en","type":"dataset","venue":"Ocean Networks Canada Society","topic":"Data Management and Algorithms","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"China; Software deployment; Power (physics); Quality (philosophy); Quality assurance","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000461277,0.0006755061,0.0006603822,0.0000451544,0.0003605915,0.0009654767,0.004770845,0.000408343,0.0001398475],"category_scores_gemma":[0.0000138587,0.0007113808,0.0003898398,0.0006397661,0.00008844459,0.000674873,0.001722567,0.000982594,0.00001590073],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003853238,"about_ca_system_score_gemma":0.001023422,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.5256459,"about_ca_topic_score_gemma":0.4740956,"domain_scores_codex":[0.9958002,0.00009298091,0.0005188373,0.001275339,0.001124874,0.001187748],"domain_scores_gemma":[0.996332,0.00009364661,0.0003912039,0.002758366,0.00007815793,0.0003466046],"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":[0.000001447517,0.00003492674,0.00005940536,0.00005083333,0.0001757918,0.00007343037,0.00001458347,0.001068382,2.106448e-8,0.00006213581,0.9977505,0.0007085508],"study_design_scores_gemma":[0.0003735208,0.00004032,0.00106087,0.00007229314,0.00006777697,0.000007591899,0.00001884463,0.03039735,1.460352e-7,0.0000221088,0.9671186,0.000820544],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00002015411,0.0006958078,0.01301517,0.001143472,0.005678939,0.0005544951,0.9786841,0.0001489267,0.00005899322],"genre_scores_gemma":[0.0001753031,0.0008687912,0.002207649,0.004546518,0.0006975998,0.000006771242,0.9875839,0.00005863072,0.003854875],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.05155028,"threshold_uncertainty_score":0.9995337,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005147094327091184,"score_gpt":0.1930403132379103,"score_spread":0.1878932189108191,"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."}}