{"id":"W3158311660","doi":"10.1029/2021gl093126","title":"Thank You to Our 2020 Peer Reviewers","year":2021,"lang":"en","type":"article","venue":"Geophysical Research Letters","topic":"Scientific Research and Technology","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Peer review; Data science; Computer science; Political 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":[{"model":"gemma","categories":[],"domain":null,"study_design":"not_applicable","genre":"editorial","about_ca_system":false,"about_ca_topic":false,"confidence":"low","status":"direct model label, unvalidated"},{"model":"gpt","categories":[],"domain":null,"study_design":"not_applicable","genre":"editorial","about_ca_system":false,"about_ca_topic":false,"confidence":"high","status":"direct model label, unvalidated"}],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.002320459,0.0001547128,0.0002584771,0.0002997482,0.0003118892,0.0005941464,0.002643056,0.00005676518,0.00005225554],"category_scores_gemma":[0.00420413,0.0001353493,0.0001559304,0.004113924,0.0001606872,0.0003610239,0.002283582,0.0009352305,0.005817],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001210694,"about_ca_system_score_gemma":0.0002887961,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009764399,"about_ca_topic_score_gemma":0.00001465402,"domain_scores_codex":[0.9934708,0.0005220225,0.0002243264,0.001097161,0.003202773,0.001482847],"domain_scores_gemma":[0.9962351,0.0002769533,0.00002435378,0.001780232,0.001046191,0.0006371671],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001171231,0.0001083527,0.00007336847,0.00002525162,0.0000223882,0.000962575,0.0001692977,0.000004903709,0.1042397,0.02120862,0.8032745,0.06989938],"study_design_scores_gemma":[0.0004424741,0.0002321746,0.004394085,0.00008244289,0.00000274572,0.00004397942,0.0003007934,0.001241223,0.05645401,0.01224799,0.9241159,0.0004421648],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.1358536,0.000281333,0.03409977,0.8238549,0.00122945,0.0005802553,0.00001019194,0.0002949099,0.003795675],"genre_scores_gemma":[0.9193339,0.0001613233,0.03349871,0.01527444,0.001361548,0.0003170832,0.00002614141,0.00004640985,0.02998049],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8085804,"threshold_uncertainty_score":0.9949571,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06216291538224569,"score_gpt":0.3761836360795861,"score_spread":0.3140207206973404,"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."}}