{"id":"W6964374724","doi":"10.25602/gold.v.v2i2.1352.g1471","title":"Review: Gregory Mackie, Beautiful Untrue Things: Forging Oscar Wilde’s Extraordinary Afterlife (Toronto: University of Toronto Press, 2019)","year":2019,"lang":"en","type":"article","venue":"Goldsmiths (University of London)","topic":"Forest Ecology and Biodiversity Studies","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Afterlife; Forging; Forge; George (robot); 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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0002781764,0.000221004,0.0005562771,0.000007407023,0.0003687737,0.000006677945,0.0007623924,0.0002070312,0.002923121],"category_scores_gemma":[0.00001554967,0.0001472635,0.000311942,0.00009803506,0.0003495346,0.001073926,0.0005578855,0.0001385378,0.00008913015],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001599472,"about_ca_system_score_gemma":0.00002487821,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.04793665,"about_ca_topic_score_gemma":0.03608187,"domain_scores_codex":[0.998656,0.0001235992,0.0001649891,0.000444931,0.0002497874,0.0003606938],"domain_scores_gemma":[0.9990633,0.0001391247,0.0003227342,0.000183511,0.0001729093,0.0001183963],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.001741763,0.0009057187,0.3960578,0.002024523,0.0009809966,0.0001882708,0.004405361,0.00001390716,0.006982838,0.002181763,0.5353181,0.049199],"study_design_scores_gemma":[0.001058394,0.000816383,0.5097713,0.0006801459,0.0003079986,0.00001261885,0.009223496,0.00004538479,0.00007617185,0.00008028751,0.4773944,0.0005333932],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.913219,0.07015155,0.00000850815,0.002027108,0.0003408283,0.0007823076,0.0003318415,0.0001183402,0.01302053],"genre_scores_gemma":[0.8570651,0.126138,0.0007059774,0.0006478403,0.00007504922,2.535182e-7,0.0001341667,0.000003776868,0.01522992],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1137135,"threshold_uncertainty_score":0.9979883,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007054705982179242,"score_gpt":0.1736631554304954,"score_spread":0.1666084494483162,"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."}}