{"id":"W2902347989","doi":"10.3389/fevo.2018.00201","title":"Snapshot Surveys for Lake Monitoring, More Than a Shot in the Dark","year":2018,"lang":"en","type":"article","venue":"Frontiers in Ecology and Evolution","topic":"Fish Ecology and Management Studies","field":"Environmental Science","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Staatssekretariat für Bildung, Forschung und Innovation; Université de Genève; Global Lake Ecological Observatory Network","keywords":"Macroecology; Snapshot (computer storage); Biogeography; Ecology; Geography; Environmental science; Biology; Computer science","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001129408,0.0000785972,0.0001144488,0.00005586422,0.0002393025,0.000005389053,0.0001360199,0.0001022522,0.00005507148],"category_scores_gemma":[0.00008344775,0.00006397535,0.0000165079,0.0001401624,0.0005078642,0.0001112574,0.00008822123,0.00009220913,0.000009351756],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000920497,"about_ca_system_score_gemma":0.000004064171,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005712513,"about_ca_topic_score_gemma":0.0384979,"domain_scores_codex":[0.9991933,0.0001684493,0.0001165619,0.0002109648,0.00004936093,0.000261371],"domain_scores_gemma":[0.9997835,0.00006419363,0.00003532178,0.00009855978,0.000004300633,0.00001411492],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00003014513,0.00004638635,0.9177752,0.000003959545,0.000008834461,0.000001623219,0.0006820571,0.0000264329,0.000003892353,0.00009516699,0.0811411,0.0001851757],"study_design_scores_gemma":[0.0003875892,0.0001526802,0.9891824,0.000003000958,0.000009492908,0.000001190784,0.001112287,0.0003571963,0.000004378182,0.004623956,0.004095073,0.00007074858],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9887258,0.00004740494,0.001337664,0.00122003,0.001256835,0.0003918755,0.000004453079,0.000008989208,0.007006966],"genre_scores_gemma":[0.9983443,0.00005167017,0.0008997354,0.0002370952,0.00006403388,0.0001444339,0.00001021848,0.000003255754,0.0002452501],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07704602,"threshold_uncertainty_score":0.979047,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01299553848833513,"score_gpt":0.2420663387410546,"score_spread":0.2290708002527195,"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."}}