{"id":"W4404316664","doi":"10.1525/rep.2024.168.5.88","title":"Seizing the Memes of Extraction","year":2024,"lang":"en","type":"article","venue":"Representations","topic":"Digital Games and Media","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Extraction (chemistry); History; Chemistry; Chromatography","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":[],"consensus_categories":[],"category_scores_codex":[0.0001470859,0.00001670843,0.00002378102,0.00002235867,0.00006022962,0.0000700103,0.00005068037,0.00001205567,0.0001124319],"category_scores_gemma":[0.0001468264,0.00001169531,0.00003435311,0.0001938698,0.00008758833,0.0001845776,0.00000794927,0.0000319372,0.00002817357],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001052303,"about_ca_system_score_gemma":0.00006307851,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004269401,"about_ca_topic_score_gemma":0.0003329115,"domain_scores_codex":[0.9996722,0.00002591115,0.00006078897,0.0000528473,0.0001323422,0.00005596415],"domain_scores_gemma":[0.9996542,0.000228055,0.00001328812,0.00006072152,0.00002462235,0.00001907549],"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":[0.000001455558,0.00002465391,0.0007806063,0.00001666369,0.00003238003,0.000004213599,0.05186331,0.00007140754,0.001370619,0.4899676,0.0132778,0.4425893],"study_design_scores_gemma":[0.00001459335,0.000003435108,0.002232966,0.00001619006,0.00001205264,7.71101e-7,0.01890996,0.00009547584,0.0004071654,0.003246336,0.9750392,0.00002187402],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.02360096,0.0005970883,0.0005914049,0.005823789,0.0006061418,0.0001047125,0.000003979386,0.00005821138,0.9686137],"genre_scores_gemma":[0.948457,0.0001520561,0.00008406972,0.00002167242,0.0001564459,0.000008285633,0.000001804287,0.000002353191,0.0511163],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.9617614,"threshold_uncertainty_score":0.1231051,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04963018635342425,"score_gpt":0.4212981156367028,"score_spread":0.3716679292832785,"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."}}