{"id":"W4296444191","doi":"10.1145/3561799","title":"From Zero to One Hundred","year":2022,"lang":"en","type":"article","venue":"Queue","topic":"Information and Cyber Security","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Zero (linguistics); Praise; Computer security; Key (lock); Computer science; Psychology","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":[0.0001019692,0.00003417967,0.00005225683,0.00004048531,0.0001410241,0.00006338444,0.0005223821,0.00001024046,0.0002949606],"category_scores_gemma":[0.000007599393,0.00004406519,0.00002139793,0.0002057762,0.000003931134,0.0001985426,0.0003881488,0.00008276462,0.0004869545],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003997903,"about_ca_system_score_gemma":0.00003203762,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003005516,"about_ca_topic_score_gemma":0.00001507138,"domain_scores_codex":[0.9994548,0.00003094037,0.00009500136,0.000109465,0.0002035218,0.0001062598],"domain_scores_gemma":[0.9995916,0.00001441726,0.00002365863,0.000295662,0.00001797776,0.00005672515],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001140318,0.0001279522,0.00007275536,0.000003340012,0.00001726045,0.00001162458,0.02997834,0.0004387393,0.0007590284,0.7738658,0.06229807,0.1324157],"study_design_scores_gemma":[0.0006351887,0.0001739056,0.007738916,0.000005726693,0.000003730735,0.000008082502,0.0003638292,0.0254699,0.005801081,0.06860767,0.8907861,0.0004059334],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1165703,0.00003932859,0.8203664,0.009934421,0.001483741,0.0002441186,0.00003616232,0.0004073931,0.05091815],"genre_scores_gemma":[0.9818306,3.858891e-7,0.01099277,0.006679134,0.00004248705,0.00002555988,0.000009724771,0.000002415263,0.0004169158],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8652604,"threshold_uncertainty_score":0.6258977,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01539724640209786,"score_gpt":0.2285028495226239,"score_spread":0.2131056031205261,"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."}}