{"id":"W4250984856","doi":"10.32920/14639064.v1","title":"Visualization of Lake Mead Surface Area Changes from 1972 to 2009","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Hydrology and Watershed Management Studies","field":"Environmental Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Satellite; Period (music); Surface water; Physical geography; Satellite imagery; Hydrology (agriculture); Geology; Environmental science; Geography; Remote sensing","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":[0.00007199148,0.000159131,0.00008630702,0.001831179,0.0002450966,0.0004194494,0.00009500571,0.0001709191,0.00261023],"category_scores_gemma":[0.000146481,0.00008486322,0.0001421063,0.001647826,0.00008594974,0.0002184055,0.0002364914,0.0001753081,0.0004060363],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003826722,"about_ca_system_score_gemma":0.0002484967,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03545818,"about_ca_topic_score_gemma":0.1007718,"domain_scores_codex":[0.9999553,0.00000251499,0.000001831655,0.00001165406,0.00001520859,0.00001347693],"domain_scores_gemma":[0.9999139,0.000009118042,0.00002258602,0.000004485616,0.00002993034,0.00001996782],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0006299053,0.000178659,0.8035446,0.0002362706,0.0002472505,0.001154627,0.002198267,0.008300082,0.0517079,0.00102308,0.0368575,0.09392186],"study_design_scores_gemma":[0.000006011287,0.0000118085,0.9894115,0.000009544598,0.000009896751,0.00006458454,0.0002472692,0.002022711,0.001303675,0.00002935542,0.006876655,0.000006991273],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9758635,0.0002430217,0.0004320403,0.0001391542,0.00001984383,0.00001241615,0.0101684,0.0002882541,0.01283335],"genre_scores_gemma":[0.9870111,0.0002348535,0.001318997,0.0000237453,0.00002100962,0.00001025155,0.008501676,0.00004901843,0.002829254],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03545818,"threshold_uncertainty_score":0.07050359,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02468254994456297,"score_gpt":0.2553568449133669,"score_spread":0.2306742949688039,"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."}}