{"id":"W7119892105","doi":"10.34943/58c1d2fd-7956-459c-8f1e-82ba371c8421","title":"Endeavour North Bottom Pressure Recorder Deployed 2020-09-10","year":2020,"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":[0.0008852063,0.001545342,0.0009727413,0.002432023,0.0008782956,0.001518706,0.002582322,0.001196398,0.02435969],"category_scores_gemma":[0.002768397,0.0005047022,0.000569683,0.004999245,0.0004348593,0.001024399,0.001341469,0.001238884,0.04075744],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002654723,"about_ca_system_score_gemma":0.004573129,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.3775066,"about_ca_topic_score_gemma":0.5470176,"domain_scores_codex":[0.9991857,0.00006943568,0.00006202463,0.0002235762,0.000305261,0.0001538915],"domain_scores_gemma":[0.9983923,0.0001054965,0.00009716808,0.0002880984,0.0009051311,0.000211891],"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":[0.00004979378,0.00001555151,0.001401505,0.0001296877,0.00001448564,0.00002808928,0.00001979842,0.0003514212,0.0001578922,0.0003437326,0.9953523,0.002135755],"study_design_scores_gemma":[0.0001291524,0.00001702604,0.01604546,0.0001673595,0.00001819213,0.00006042176,0.0001463222,0.001313929,0.0006148411,0.0008468074,0.9805917,0.00004878655],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0002868811,0.00002432042,0.00008701648,0.0000518702,0.00001900239,0.00001043521,0.9981516,0.0003006067,0.001068288],"genre_scores_gemma":[0.0004570658,0.00001444379,0.0002173557,0.00001944049,0.000003659552,0.00002192764,0.998494,0.00003307563,0.0007390011],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.6224934,"threshold_uncertainty_score":0.7506186,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007355006922168754,"score_gpt":0.199345311893863,"score_spread":0.1919903049716942,"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."}}