{"id":"W6996935134","doi":"","title":"Time-Frequency analysis of long-term marine data from Cambridge Bay in the Canadian Arctic. High resolution ADCP, CTD and Fluorometer time series analysis","year":2017,"lang":"en","type":"other","venue":"Open Research Online (The Open University)","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Time series; Series (stratigraphy); Mode (computer interface); Bay; Wind wave; Range (aeronautics); High resolution; Shore","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","scholarly_communication","open_science","insufficient_payload"],"consensus_categories":["open_science","insufficient_payload"],"category_scores_codex":[0.00650535,0.0006258661,0.001931235,0.01119315,0.001249824,0.001980653,0.02661041,0.0004967568,0.01498727],"category_scores_gemma":[0.0008078331,0.0004853584,0.0002585296,0.01313781,0.002029032,0.001967133,0.01757201,0.001467054,0.0009683119],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001369501,"about_ca_system_score_gemma":0.002389936,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9629443,"about_ca_topic_score_gemma":0.9955334,"domain_scores_codex":[0.9906338,0.004183352,0.0005141295,0.001934228,0.001588729,0.001145709],"domain_scores_gemma":[0.9886026,0.0006372625,0.0008039241,0.008763308,0.0006759056,0.0005169609],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.002790752,0.001710603,0.2884795,0.0001895599,0.0859714,0.005787639,0.0007465865,0.0001550307,0.0003109858,0.002767555,0.6049536,0.006136771],"study_design_scores_gemma":[0.001906109,0.0002016892,0.6673608,0.0004239589,0.01443174,0.000007124934,0.0003062911,0.002817306,0.000005141258,0.00004939935,0.3115211,0.000969296],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.02517301,0.0003234487,0.000008094995,0.003852592,0.00005343387,0.006649983,0.09064103,0.00005677159,0.8732417],"genre_scores_gemma":[0.01049206,0.0007618608,0.001799842,0.0000430386,0.0001160563,0.00001270161,0.06775535,0.0003959049,0.9186232],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.3788813,"threshold_uncertainty_score":0.9998096,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09923269388961642,"score_gpt":0.3578573736485186,"score_spread":0.2586246797589022,"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."}}