{"id":"W4393629158","doi":"10.5281/zenodo.6977161","title":"Processing and Data for \"Estimating ocean net primary productivity from daily cycles of carbon biomass measured by profiling floats\"","year":2021,"lang":"en","type":"dataset","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Atmospheric and Environmental Gas Dynamics","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"","keywords":"Primary productivity; Primary production; Profiling (computer programming); Environmental science; Biomass (ecology); Productivity; Oceanography; Forestry; Geography; Computer science; Geology; Ecology; Biology; Economics; Nutrient; Ecosystem","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009512968,0.001810711,0.0008913417,0.001911633,0.0006182978,0.001454159,0.002104617,0.001014045,0.117303],"category_scores_gemma":[0.00315647,0.0006680447,0.001189298,0.003647069,0.0003144569,0.00169812,0.001677774,0.001626177,0.1328365],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009538688,"about_ca_system_score_gemma":0.001622168,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01892492,"about_ca_topic_score_gemma":0.0201926,"domain_scores_codex":[0.9992365,0.00006772361,0.0001020503,0.0002433821,0.0002265827,0.0001238425],"domain_scores_gemma":[0.9983328,0.0002793721,0.0001512735,0.0003921618,0.0006964309,0.0001479154],"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":[0.00006383,0.00002336732,0.001085197,0.0002838942,0.00001957639,0.00002307598,0.00002033818,0.000623025,0.0003946769,0.0003194859,0.9922515,0.004892032],"study_design_scores_gemma":[0.000341458,0.00003726135,0.01105253,0.0002850462,0.00002527985,0.00005463604,0.0001340473,0.002581883,0.002768623,0.002268147,0.9803868,0.00006433102],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0002502681,0.0000118685,0.000407264,0.00005177436,0.00002537083,0.00003085141,0.9953281,0.003178748,0.0007157826],"genre_scores_gemma":[0.000550885,0.00002113526,0.001490503,0.0000478472,0.000009255448,0.0001600491,0.9963898,0.0006541706,0.0006762267],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.117303,"threshold_uncertainty_score":0.3924177,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02680255932650344,"score_gpt":0.2347427772777022,"score_spread":0.2079402179511988,"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."}}