{"id":"W7067838894","doi":"","title":"NHL analyst Darren Dreger","year":2024,"lang":"en","type":"other","venue":"Bulletin of Miscellaneous Information (Royal Gardens Kew)","topic":"Computational Physics and Python Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Feature (linguistics); Noise (video); Context (archaeology); Power (physics)","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":[0.0001371139,0.0002558798,0.000287503,0.0001215206,0.00004289646,0.0001803928,0.0007332127,0.0001728945,0.07436702],"category_scores_gemma":[0.00001659241,0.0002517582,0.0001860055,0.00002866285,0.00006148855,2.838077e-7,0.0002331415,0.0002149993,0.05213508],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003071649,"about_ca_system_score_gemma":0.00004839153,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001215803,"about_ca_topic_score_gemma":0.0002228158,"domain_scores_codex":[0.9986051,0.00003222996,0.0004562851,0.0002848335,0.0004248678,0.0001966634],"domain_scores_gemma":[0.9987617,0.00006973346,0.0003359772,0.000602153,0.0001298123,0.0001005923],"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":[0.000002838575,0.00002450607,1.201084e-7,0.0001723502,0.00006559076,0.000005414953,0.00009092953,0.0002769193,1.349405e-7,0.007660837,0.9878472,0.003853138],"study_design_scores_gemma":[0.0001114479,0.00002627682,0.000003070795,0.0001235104,0.00003284588,0.00002052011,0.000008278795,0.0008963466,0.000002277445,0.001072173,0.9974447,0.0002585684],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.00000111103,0.000420938,0.0002563478,0.0005832149,0.0003327585,0.0002481298,0.0001043859,0.0003424321,0.9977107],"genre_scores_gemma":[0.0004723801,0.00005138377,0.007012031,0.000262059,0.0002061762,0.00002202932,0.0001313062,0.00008273806,0.9917599],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.02223193,"threshold_uncertainty_score":0.9999934,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006208802251701288,"score_gpt":0.2004409565317644,"score_spread":0.1942321542800632,"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."}}