{"id":"W7106827669","doi":"10.34943/5d4ee5c3-bdae-41cc-b241-b3888770b818","title":"Endeavour South Bottom Pressure Recorder Deployed 2011-09-16","year":2024,"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 logger; Pacific ocean; Data quality","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":[0.0009621259,0.001435884,0.0009799541,0.002671687,0.001018797,0.001573201,0.002346954,0.00123015,0.02339664],"category_scores_gemma":[0.003552435,0.0004863083,0.0005889502,0.005200739,0.0004396459,0.0008586944,0.00136631,0.001264942,0.03984121],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003076433,"about_ca_system_score_gemma":0.005754427,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.4565812,"about_ca_topic_score_gemma":0.6500613,"domain_scores_codex":[0.9991177,0.00007957686,0.00007170087,0.0002171523,0.0003367747,0.0001770315],"domain_scores_gemma":[0.9979402,0.0001578035,0.0001263759,0.0003013026,0.001226487,0.0002477701],"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":[0.00005564994,0.00001592906,0.001824078,0.0001340853,0.00001515255,0.00002972656,0.00002297972,0.0002920989,0.000108801,0.0002812634,0.9953855,0.001834743],"study_design_scores_gemma":[0.0001632055,0.00002269066,0.02400894,0.0002360503,0.00002291004,0.00006526108,0.0002288539,0.001078387,0.0005150319,0.0007290539,0.9728752,0.00005435239],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0003764666,0.00002398156,0.00005431899,0.00006484592,0.00001906798,0.00001063588,0.9983317,0.0001641921,0.0009548616],"genre_scores_gemma":[0.0005165118,0.00001472468,0.000145792,0.00001978007,0.000004365778,0.00002484564,0.998202,0.00002675052,0.001045179],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.4565812,"threshold_uncertainty_score":0.9078473,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007567902894148886,"score_gpt":0.2087869724900211,"score_spread":0.2012190695958723,"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."}}