{"id":"W7020032020","doi":"","title":"Introducing The AmberMac Show","year":2025,"lang":"en","type":"other","venue":"Internet Archive (Internet Archive)","topic":"Radio, Podcasts, and Digital Media","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Favourite; Production (economics); Key (lock)","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":[0.0005858611,0.0007547446,0.0008031681,0.0006613714,0.0001573131,0.0005729877,0.002616157,0.0002694677,0.01392212],"category_scores_gemma":[0.000830291,0.0005892151,0.0005818686,0.0002529407,0.002065197,0.0001589596,0.0008770698,0.001213017,0.002607115],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001327898,"about_ca_system_score_gemma":0.0005315539,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.1055589,"about_ca_topic_score_gemma":0.2090645,"domain_scores_codex":[0.9951868,0.0009209393,0.000656266,0.001197276,0.0008770839,0.001161622],"domain_scores_gemma":[0.9967232,0.00135895,0.0004467195,0.0009942657,0.00005471452,0.0004221823],"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":[0.00007337228,0.00007970718,0.0003669661,0.0000730004,0.0003350849,0.0000707059,0.0165736,0.000002630562,0.00001051713,0.04835806,0.9261652,0.0078912],"study_design_scores_gemma":[0.0003489892,0.0000882192,0.0001895649,0.001065815,0.00009898227,0.00001188905,0.0008543906,0.000219508,0.00003432433,0.005433843,0.9910505,0.0006039682],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.0001283589,0.0009496673,0.004328859,0.001662148,0.004516229,0.00105084,0.0005609361,0.0005194129,0.9862835],"genre_scores_gemma":[0.0117733,0.0006636947,0.0006968873,0.001217459,0.004872189,0.0001083251,0.0002439988,0.0003393393,0.9800848],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.1035056,"threshold_uncertainty_score":0.9996559,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01425588354177311,"score_gpt":0.2701188419775758,"score_spread":0.2558629584358027,"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."}}