{"id":"W7124453801","doi":"10.34943/4bebf3cf-1d5c-488e-b805-e3df8e015b8e","title":"Endeavour North Bottom Pressure Recorder Deployed 2021-08-24","year":2021,"lang":"en","type":"dataset","venue":"Ocean Networks Canada Society","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Ocean bottom; Software deployment; Hydrothermal vent; Pressure sensor; Data quality; Pacific ocean; Pressure measurement","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000855414,0.001490114,0.001069953,0.002290183,0.0009751674,0.001549669,0.002642314,0.001279663,0.02671677],"category_scores_gemma":[0.002899487,0.0004925585,0.0005443751,0.004591282,0.0004360059,0.000999755,0.001335132,0.001277799,0.04421156],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002583815,"about_ca_system_score_gemma":0.004211785,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.3469178,"about_ca_topic_score_gemma":0.5308533,"domain_scores_codex":[0.9991724,0.00007644775,0.00005995866,0.000230672,0.0003002041,0.0001603816],"domain_scores_gemma":[0.99841,0.0001271209,0.00009661906,0.0002907968,0.0008712384,0.0002041415],"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":[0.00004937574,0.0000161819,0.001361481,0.0001232404,0.00001337002,0.00002867507,0.00002055968,0.0003701349,0.0001501681,0.0003078794,0.9955171,0.002042],"study_design_scores_gemma":[0.0001610037,0.00001820472,0.01553014,0.0001798776,0.00001738682,0.00005879144,0.0001601087,0.001442089,0.0005971644,0.0008935088,0.9808893,0.00005252574],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0002968448,0.00002086429,0.00009012937,0.00005514718,0.00001781142,0.00001174166,0.9981858,0.0003084011,0.001013315],"genre_scores_gemma":[0.0004639976,0.00001210889,0.0002255762,0.0000189783,0.000003717335,0.00002609673,0.9984838,0.00003735978,0.0007283773],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.3469178,"threshold_uncertainty_score":0.689797,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007653405149541603,"score_gpt":0.2008778014900542,"score_spread":0.1932243963405126,"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."}}