{"id":"W6945236346","doi":"10.24385/lincoln.25162595","title":"Small Machine Talks","year":2024,"lang":"en","type":"other","venue":"Lincoln Repository (University of Lincoln)","topic":"Data Management and Algorithms","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Work (physics); Key (lock); Government (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":[],"category_scores_codex":[0.0001968813,0.0003482558,0.000499418,0.0005211345,0.0001249727,0.00016716,0.002593516,0.0003468858,0.0002258639],"category_scores_gemma":[0.000005287337,0.0004116272,0.0002846226,0.0005556851,0.0001488111,0.0002874426,0.001815382,0.0003865093,0.0008877238],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008718191,"about_ca_system_score_gemma":0.0001201919,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001561823,"about_ca_topic_score_gemma":0.0004414006,"domain_scores_codex":[0.9980969,0.00008062449,0.0002260307,0.0008828656,0.0004101897,0.0003034104],"domain_scores_gemma":[0.9980507,0.00003170593,0.000388222,0.001316821,0.00005389314,0.0001586331],"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":[0.00001423947,0.0002131377,0.00006405538,0.0007692539,0.0004620097,0.002466248,0.0003919321,0.000008299301,0.00003960813,0.01324906,0.9597527,0.02256949],"study_design_scores_gemma":[0.0003586211,0.00009669534,0.00003825719,0.000413571,0.0001458638,0.00002182918,0.00009698846,0.006921755,0.00002498657,0.000362441,0.9910754,0.0004436143],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.00001105538,0.002588623,0.07153702,0.000351228,0.003034878,0.0004598945,0.00009400918,0.0009745398,0.9209487],"genre_scores_gemma":[0.0001952374,0.0001826493,0.05100582,0.00005008333,0.0004530089,9.351735e-7,0.00004728668,0.0001562329,0.9479088],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.03132272,"threshold_uncertainty_score":0.9998902,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01108943783036026,"score_gpt":0.1810510820432166,"score_spread":0.1699616442128563,"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."}}