{"id":"W2008658839","doi":"10.1080/14634981003799745","title":"Use of satellite remote sensing tools for the Great Lakes","year":2010,"lang":"en","type":"article","venue":"Aquatic Ecosystem Health & Management","topic":"Fish Ecology and Management Studies","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"European Space Agency; International Association for Great Lakes Research","keywords":"Environmental science; Buoy; Colored dissolved organic matter; Satellite; Upwelling; Remote sensing; Phytoplankton; Oceanography; SeaWiFS; Precipitation; Chlorophyll a; Meteorology; Geology; Geography; Ecology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007591061,0.0003991364,0.0001735701,0.002118068,0.0004098532,0.0006848054,0.0003770796,0.0002130013,0.005646619],"category_scores_gemma":[0.001720477,0.0001817381,0.0002342041,0.003418171,0.0001487182,0.0006477624,0.0006989218,0.0002816028,0.001830002],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007495942,"about_ca_system_score_gemma":0.001126506,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.08177193,"about_ca_topic_score_gemma":0.0765011,"domain_scores_codex":[0.9994513,0.00009283917,0.00003747935,0.0000721594,0.0003139065,0.00003222668],"domain_scores_gemma":[0.9994773,0.00007943018,0.0000829588,0.00009376781,0.0002315439,0.00003505896],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0001009498,0.00004905235,0.0519671,0.0005407904,0.0001465599,0.0005499484,0.001441446,0.006626607,0.01577014,0.007802952,0.1664195,0.748585],"study_design_scores_gemma":[0.00007427384,0.00005509876,0.2321194,0.000273474,0.0001172248,0.0004549095,0.0006954652,0.03044174,0.005014443,0.004896383,0.7257711,0.00008655282],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1818388,0.01391685,0.3133261,0.00454723,0.0008875983,0.001842741,0.1499931,0.02898816,0.3046594],"genre_scores_gemma":[0.4773587,0.006235652,0.4188375,0.000852684,0.0003394867,0.001119488,0.05504465,0.001142622,0.03906925],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9182281,"threshold_uncertainty_score":0.1625919,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04073079482071938,"score_gpt":0.2679532608787381,"score_spread":0.2272224660580187,"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."}}