{"id":"W2962827351","doi":"10.22148/16.042","title":"TED Talks as Data","year":2019,"lang":"en","type":"article","venue":"Journal of Cultural Analytics","topic":"Educational Tools and Methods","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Event (particle physics); Currency; Inclusion (mineral); Political science; Telecommunications; History; Computer science; Sociology; Gender studies; Linguistics; Philosophy; Physics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001102751,0.0000512761,0.0001445983,0.00003182354,0.0001009629,0.0000870779,0.0005154965,0.00004884376,0.0007886895],"category_scores_gemma":[0.0008197467,0.0000332426,0.00007234731,0.0002121484,0.0000502221,0.0005322381,0.00004344733,0.0001625508,0.00009323486],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005503613,"about_ca_system_score_gemma":0.0003510116,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001356788,"about_ca_topic_score_gemma":0.00005394719,"domain_scores_codex":[0.9990132,0.000102783,0.0002437673,0.00007421265,0.0004378356,0.0001281887],"domain_scores_gemma":[0.998891,0.0001348004,0.0002587432,0.0001502314,0.0004389955,0.0001262462],"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":[0.0001900202,0.0007666349,0.0629693,0.00008181465,0.001032524,0.00008190089,0.03699301,0.0009164061,0.009700141,0.2718472,0.5056348,0.1097863],"study_design_scores_gemma":[0.000157751,0.00005162622,0.003556553,0.00002744854,0.00005376196,0.00002067396,0.009133806,0.000109042,0.00005979764,0.003296093,0.9834533,0.00008019167],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8078258,0.0005926427,0.0001213268,0.01539847,0.002005544,0.000102233,0.000009636185,0.00001111698,0.1739332],"genre_scores_gemma":[0.911895,0.0006648368,0.009693711,0.0006711421,0.001811854,1.492138e-7,0.00001137806,0.000005831156,0.07524605],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4778185,"threshold_uncertainty_score":0.8635597,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1789138058291203,"score_gpt":0.4915616461961003,"score_spread":0.31264784036698,"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."}}