{"id":"W7040105761","doi":"","title":"Nukes, Storms & Fighting Back","year":2011,"lang":"en","type":"other","venue":"Bulletin of Miscellaneous Information (Royal Gardens Kew)","topic":"Mathematics, Computing, and Information Processing","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Watson; Whaling; Storm; Fishing; Feature (linguistics)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0004436669,0.0004390762,0.00052813,0.0001781168,0.0001293778,0.0002370648,0.00131193,0.0003920445,0.321304],"category_scores_gemma":[0.0001539606,0.0004075346,0.0001836561,0.00002196031,0.00009775098,0.000002181906,0.000351189,0.0003291324,0.05487385],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005225352,"about_ca_system_score_gemma":0.00007208207,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009885349,"about_ca_topic_score_gemma":0.0002103189,"domain_scores_codex":[0.9975412,0.00005345298,0.001133348,0.0002710278,0.000569477,0.0004314838],"domain_scores_gemma":[0.9970179,0.00009304512,0.00166225,0.0008170056,0.00024949,0.0001603416],"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":[0.000004362244,0.00003146383,7.344378e-7,0.001079393,0.00003465508,0.000002163032,0.001220247,0.00005756655,6.766274e-8,0.0009115462,0.9910494,0.005608411],"study_design_scores_gemma":[0.0002961019,0.0000418591,0.000001381512,0.0005905842,0.00001559994,0.00006880976,0.00004002418,0.0006833165,0.000009560299,0.0001437311,0.9976445,0.0004645221],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.000003423228,0.0002650722,0.001536588,0.00005675415,0.0005698045,0.0003233512,0.00001926315,0.0004701095,0.9967557],"genre_scores_gemma":[0.00005411412,0.00008823405,0.06946541,0.0003824179,0.0001592435,0.000006923837,0.00005871507,0.00008492308,0.9297],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.2664301,"threshold_uncertainty_score":0.9998376,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01244464624507052,"score_gpt":0.1921030415418055,"score_spread":0.1796583952967349,"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."}}