{"id":"W2887307500","doi":"10.5194/os-14-751-2018","title":"An evaluation of the performance of Sea-Bird Scientific's SeaFET™ autonomous pH sensor: considerations for the broader oceanographic community","year":2018,"lang":"en","type":"article","venue":"Ocean science","topic":"Ocean Acidification Effects and Responses","field":"Earth and Planetary Sciences","cited_by":26,"is_retracted":false,"has_abstract":true,"ca_institutions":"Tula Foundation","funders":"Hakai Institute; Division of Ocean Sciences; Pacific Salmon Foundation; Tula Foundation","keywords":"Environmental science; Seawater; Calibration; Oceanography; Bay; Range (aeronautics); Remote sensing; Shore; Computer science; Geology; Statistics; Engineering","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":["sts"],"category_scores_codex":[0.008373817,0.000100267,0.0001142606,0.0001563145,0.003273379,0.0001728846,0.0008107402,0.0000344184,0.0001892563],"category_scores_gemma":[0.0008070685,0.00005385579,0.00006395023,0.001139613,0.005521669,0.0004762193,0.00002773731,0.0001139292,0.000008271209],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000008714308,"about_ca_system_score_gemma":0.0007310659,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002113294,"about_ca_topic_score_gemma":0.0006629575,"domain_scores_codex":[0.9978451,0.0005147403,0.0002731412,0.0002360545,0.0008851095,0.0002459082],"domain_scores_gemma":[0.9967847,0.0008803576,0.000239136,0.0008732423,0.001147287,0.00007531646],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001283881,0.0002465057,0.9042789,0.00008574174,0.00003490419,1.271994e-7,0.007655959,0.0262012,0.02856479,0.0007186567,0.001386949,0.03069787],"study_design_scores_gemma":[0.0001886269,0.0001873079,0.596387,0.00001534899,0.00003527378,0.000006950452,0.0006263106,0.3694954,0.03254012,0.0002624296,0.0001841354,0.00007110485],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9978301,0.00008133062,0.00005113109,0.0003303083,0.0005791818,0.0006001753,0.00009184246,0.0000255383,0.0004104212],"genre_scores_gemma":[0.9992745,0.0000053574,0.0004932618,0.0001095595,0.00004819978,9.563926e-7,0.000005544901,0.000003449831,0.00005916914],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3432941,"threshold_uncertainty_score":0.9980242,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05844242003896794,"score_gpt":0.296038421125132,"score_spread":0.237596001086164,"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."}}