{"id":"W3000714063","doi":"","title":"Advancing River Thermal Research and Modeling I","year":2019,"lang":"en","type":"article","venue":"AGU Fall Meeting 2019","topic":"Fish Ecology and Management Studies","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Institut National de la Recherche Scientifique","funders":"","keywords":"Environmental science; Computer science","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.000800715,0.00007436985,0.00009220036,0.00003090611,0.0002279605,0.00001432543,0.000135485,0.00004189007,0.0001207967],"category_scores_gemma":[0.00005314744,0.00006639881,0.0000138207,0.00008462713,0.0001324088,0.0001664205,0.0006216169,0.000150781,0.001471065],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004277686,"about_ca_system_score_gemma":0.000002333951,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009769085,"about_ca_topic_score_gemma":0.001833122,"domain_scores_codex":[0.9990469,0.00005318538,0.00009449089,0.0002728443,0.000182161,0.0003504492],"domain_scores_gemma":[0.9996657,0.0001138579,0.00002329315,0.0001531387,0.000009064274,0.00003493428],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00000993194,0.00002030202,0.979682,0.00001152145,0.00001438503,0.000002020795,0.0006516422,0.009628982,0.000750075,0.0001845441,0.008564539,0.0004800211],"study_design_scores_gemma":[0.0009838882,0.0005483636,0.9137625,0.0000999011,0.00002168752,0.000003249167,0.001853967,0.06486433,0.0001567625,0.004490402,0.01269163,0.000523349],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9023089,0.00005696354,0.0000305586,0.0004477768,0.00009349735,0.0001725359,4.418894e-7,0.00002759435,0.09686174],"genre_scores_gemma":[0.9946786,0.00006460879,0.0007599852,0.0002835935,0.00002296155,0.0000071618,8.97967e-7,0.000009083631,0.004173176],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.09268857,"threshold_uncertainty_score":0.9993064,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02092960347741897,"score_gpt":0.2704961737420101,"score_spread":0.2495665702645911,"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."}}