{"id":"W6890260310","doi":"10.34943/bd07114c-65e8-47d0-a47f-ee7d8e73aad3","title":"Dellwood Seamounts Oxygen Sensor Deployed 2018-07-07","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":"Seamount; Oxygen; Oxygen sensor; Pacific ocean; Measure (data warehouse); Software deployment","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":[0.0005236314,0.00143019,0.0007845934,0.001644767,0.0008495661,0.0009364965,0.002087146,0.001138323,0.01132865],"category_scores_gemma":[0.001907808,0.0003341199,0.0004556411,0.003087591,0.000352333,0.0008942203,0.00103356,0.001037544,0.01929893],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001798683,"about_ca_system_score_gemma":0.002706816,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.2602946,"about_ca_topic_score_gemma":0.4553572,"domain_scores_codex":[0.999428,0.00004413803,0.00004172525,0.000138094,0.0002268477,0.0001212488],"domain_scores_gemma":[0.9990817,0.00006566637,0.0000454346,0.0001598825,0.0005434039,0.0001039067],"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":[0.00006237883,0.00002603766,0.001743659,0.0001753262,0.00001439484,0.00003770652,0.00002855944,0.0005552993,0.0002333038,0.0003132905,0.9933473,0.00346258],"study_design_scores_gemma":[0.0001503277,0.0000296511,0.01939132,0.0002502617,0.00002227,0.00009948116,0.0002645419,0.002684864,0.001195874,0.001100574,0.9747577,0.00005302491],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.001079374,0.00006952901,0.0001339029,0.0001273809,0.0000518819,0.00001973213,0.9962443,0.0005343598,0.001739624],"genre_scores_gemma":[0.001432537,0.00003499973,0.0002862402,0.00003418459,0.000006746467,0.00003420246,0.9971514,0.00003604481,0.0009836622],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.7397053,"threshold_uncertainty_score":0.5175591,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01031674642991675,"score_gpt":0.2144513663251197,"score_spread":0.204134619895203,"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."}}