{"id":"W6911584472","doi":"10.5281/zenodo.12032016","title":"pdf margin of safety","year":2024,"lang":"en","type":"other","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Toll; Variety (cybernetics); Value (mathematics); Margin (machine learning); Stock (firearms); Investment (military); Profit margin","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0009971628,0.001193016,0.001114984,0.002806472,0.001801928,0.007489398,0.001397655,0.002295352,0.8525472],"category_scores_gemma":[0.00564792,0.000633003,0.0007227596,0.001992397,0.0005944712,0.003821371,0.002011982,0.002048282,0.7326651],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001383996,"about_ca_system_score_gemma":0.001616086,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004875235,"about_ca_topic_score_gemma":0.005660593,"domain_scores_codex":[0.9989163,0.00006728019,0.00004020987,0.00009789845,0.0007420883,0.0001362492],"domain_scores_gemma":[0.9953657,0.0004206245,0.0001369624,0.000522348,0.002903728,0.0006506334],"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":[0.00002888838,0.00001482983,0.00008504415,0.00004744569,0.000001355454,0.00002311088,0.00001159483,0.00008037488,0.0001758625,0.002416096,0.971183,0.02593239],"study_design_scores_gemma":[0.00001347023,0.00001784622,0.0004587037,0.00005117041,0.00000278177,0.00006499866,0.00002055775,0.0001348436,0.0002078777,0.001133709,0.9978852,0.000008821093],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.0004276702,0.0003101088,0.001203269,0.0009344366,0.00114877,0.0001138372,0.008039323,0.002777393,0.9850451],"genre_scores_gemma":[0.004095973,0.000350096,0.0005958733,0.0004280833,0.0004316439,0.00006250777,0.003591484,0.001359262,0.989085],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.1474528,"threshold_uncertainty_score":0.2103235,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.025671644079829,"score_gpt":0.2481030481141241,"score_spread":0.2224314040342951,"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."}}