{"id":"W4309421654","doi":"10.31223/x5h07q","title":"Community recommendations for geochemical data, services and analytical capabilities in the 21st century","year":2022,"lang":"en","type":"preprint","venue":"","topic":"Data Quality and Management","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"HORIZON EUROPE Framework Programme; Cambridge Trust; Eidgenössische Technische Hochschule Zürich; Gates Cambridge Trust; Nuclear Safety and Security Commission; Deutsche Forschungsgemeinschaft; Bill and Melinda Gates Foundation; European Commission; Geochemical Society; National Aeronautics and Space Administration; Natural Environment Research Council; Science Foundation Ireland; National Science Foundation","keywords":"Data science; Variety (cybernetics); Computer science; Data sharing; Data quality; Earth science; Outreach; Data curation; Quality (philosophy); Political science; Service (business); Business; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":false,"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":["open_science","insufficient_payload"],"consensus_categories":["open_science"],"category_scores_codex":[0.01839006,0.0001664129,0.0003373995,0.0001799068,0.0004536919,0.000788936,0.005494163,0.00009434234,0.001538935],"category_scores_gemma":[0.001731808,0.0001081013,0.00007153692,0.0002559036,0.0001967089,0.0003107725,0.01505056,0.0009633965,0.000009998077],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004731716,"about_ca_system_score_gemma":0.0000570581,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00530717,"about_ca_topic_score_gemma":0.007557148,"domain_scores_codex":[0.9957894,0.001817686,0.0007616178,0.0006276119,0.0007866979,0.0002169592],"domain_scores_gemma":[0.9893821,0.006592223,0.0001790427,0.003708411,0.00008334937,0.00005480217],"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":[0.0000871184,0.001233597,0.003173478,0.0007150324,0.0001376475,0.000002157766,0.02298356,0.00007197426,0.000001204961,0.4339138,0.4664886,0.07119184],"study_design_scores_gemma":[0.0001243317,0.00001638104,0.001251701,0.00001225065,0.00002782452,7.343068e-7,0.20995,0.003682616,5.030927e-7,0.1164611,0.668357,0.0001155264],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.2935941,0.001416653,0.004338464,0.4633656,0.00336882,0.007353495,0.06024955,0.0002426268,0.1660706],"genre_scores_gemma":[0.8685461,0.00257586,0.01718943,0.03417942,0.0004232236,0.001398005,0.0704255,0.0000508821,0.00521163],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5749519,"threshold_uncertainty_score":0.9998866,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3850553958374082,"score_gpt":0.475157125632406,"score_spread":0.09010172979499781,"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."}}