{"id":"W4313545906","doi":"10.1021/acssensors.2c02343","title":"An Automated Microfluidic Analyzer for <i>In Situ</i> Monitoring of Total Alkalinity","year":2023,"lang":"en","type":"article","venue":"ACS Sensors","topic":"Ocean Acidification Effects and Responses","field":"Earth and Planetary Sciences","cited_by":50,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"Natural Sciences and Engineering Research Council of Canada; Canada First Research Excellence Fund; Ocean Frontier Institute; Canada Excellence Research Chairs, Government of Canada; Canada Foundation for Innovation","keywords":"Alkalinity; Spectrum analyzer; Titration; Environmental science; Seawater; Carbon dioxide; Calibration; Process engineering; Chemistry; Computer science; Engineering; Physics; Oceanography; Geology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000376324,0.00007886687,0.0001374404,0.0001675176,0.00006493598,0.00001873827,0.00009096349,0.00005555583,0.00003241837],"category_scores_gemma":[0.00008081804,0.00006485205,0.00004237558,0.0004564816,0.00004306934,0.0001056475,0.000003430648,0.00004818159,0.00007429707],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000002278462,"about_ca_system_score_gemma":0.00002246382,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002148628,"about_ca_topic_score_gemma":0.00002834812,"domain_scores_codex":[0.9992345,0.00009794034,0.0001857661,0.0001674743,0.0001125657,0.0002017421],"domain_scores_gemma":[0.9993637,0.0003312686,0.00005516522,0.0001523786,0.00003387398,0.00006365466],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001644307,0.00003932673,0.6440307,0.00005895457,0.00002349489,0.0000192825,0.0005660763,0.009254826,0.3386426,0.000006454258,0.001594222,0.005599564],"study_design_scores_gemma":[0.0002185601,0.00009409367,0.8507749,0.00001314534,0.000007578361,0.000002882524,0.0003851125,0.01201568,0.1361673,0.00001873109,0.0002126795,0.00008932934],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9989781,0.0001734942,0.000005140658,0.00008357459,0.0002366685,0.0001537416,0.00007506457,0.0001790545,0.0001152077],"genre_scores_gemma":[0.9993823,0.00009278079,0.0001817453,0.00001404687,0.00006643539,7.544989e-7,0.00009275271,0.000004083802,0.0001650756],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2067442,"threshold_uncertainty_score":0.264459,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02209146370632089,"score_gpt":0.2873064574559512,"score_spread":0.2652149937496304,"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."}}