{"id":"W2754405429","doi":"","title":"The Dynamics of Laurentian Great Lakes Surface Energy Budgets","year":2015,"lang":"en","type":"article","venue":"2015 AGU Fall Meeting","topic":"Marine and environmental studies","field":"Earth and Planetary Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Environment and Climate Change Canada","funders":"","keywords":"Dynamics (music); Geology; Environmental science; Physics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003283523,0.00009711269,0.0001201028,0.00001095913,0.0001665448,0.000026687,0.0001773958,0.00003222651,0.00005960741],"category_scores_gemma":[0.00004644208,0.00006186772,0.00003609195,0.00006621981,0.0001040545,0.000066302,0.00004694855,0.00005177134,0.0000474593],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000007003352,"about_ca_system_score_gemma":0.00001098755,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.04063825,"about_ca_topic_score_gemma":0.5010535,"domain_scores_codex":[0.9992098,0.00005356244,0.0001599229,0.0001281733,0.0002290126,0.0002194934],"domain_scores_gemma":[0.9995831,0.0001000744,0.00008147567,0.0001317377,0.00001994943,0.00008366116],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001499762,0.000006089291,0.9656597,0.000005495323,0.00002329508,0.000002845214,0.0001736974,0.003412345,0.000004338237,0.00009681919,0.009299967,0.02130043],"study_design_scores_gemma":[0.0008707761,0.0003893644,0.4013419,0.00007031432,0.00007738081,0.0000195512,0.006320202,0.1475532,0.0001963407,0.002373274,0.4401194,0.0006682015],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8695092,0.00407477,0.00003541314,0.0007201335,0.0003619666,0.00005085852,0.00002814406,0.00002630039,0.1251932],"genre_scores_gemma":[0.9957187,0.0003620465,0.0002387495,0.00004896416,0.00006047435,3.455718e-7,0.00007679974,0.000003303147,0.003490606],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5643177,"threshold_uncertainty_score":0.9657502,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01348538087179139,"score_gpt":0.1972859763347715,"score_spread":0.1838005954629801,"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."}}