{"id":"W1975358829","doi":"10.1038/nature09951","title":"Does blending of chlorophyll data bias temporal trend?","year":2011,"lang":"en","type":"letter","venue":"Nature","topic":"Marine and coastal ecosystems","field":"Earth and Planetary Sciences","cited_by":66,"is_retracted":false,"has_abstract":false,"ca_institutions":"Fisheries and Oceans Canada","funders":"","keywords":"Phytoplankton; Biomass (ecology); Environmental science; Productivity; Primary productivity; Chlorophyll a; Ecology; Oceanography; Atmospheric sciences; Biology; Geology; Ecosystem; Economics; Botany; Nutrient","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":[0.008043666,0.0003044707,0.0006591081,0.0005247084,0.0007591944,0.001678857,0.0007689449,0.009035329,0.003993158],"category_scores_gemma":[0.06003955,0.0003315873,0.000518041,0.0009408457,0.001363616,0.002563159,0.0007918733,0.007758678,0.003503888],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001137277,"about_ca_system_score_gemma":0.0009405231,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006885348,"about_ca_topic_score_gemma":0.01198305,"domain_scores_codex":[0.9985447,0.0005130289,0.0002517053,0.0002720664,0.0003193064,0.00009923994],"domain_scores_gemma":[0.9710848,0.02111656,0.001689836,0.001312552,0.004051816,0.0007445738],"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":[0.0006128187,0.00008227403,0.03649465,0.0001537763,0.0001925618,0.001406487,0.0003445662,0.0005235594,0.0007488496,0.005677301,0.7868671,0.1668961],"study_design_scores_gemma":[0.0005384202,0.0003333194,0.06015185,0.0007994127,0.0004371298,0.005311607,0.002076628,0.01110833,0.002820475,0.08504818,0.8310965,0.0002782458],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.004538884,0.00139671,0.00193324,0.9672641,0.02042426,0.00001470723,0.0004077323,0.00009657798,0.0039238],"genre_scores_gemma":[0.08133405,0.003139094,0.004963666,0.8224083,0.07627919,0.00006980692,0.0002645995,0.0001757416,0.01136548],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.009035329,"threshold_uncertainty_score":0.04253948,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03611695532499424,"score_gpt":0.2283541485854181,"score_spread":0.1922371932604238,"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."}}