{"id":"W4398467015","doi":"10.7910/dvn/66hucd/pzmxjy","title":"media_elements.xml","year":2019,"lang":"en","type":"dataset","venue":"Harvard Dataverse","topic":"Advanced Computational Techniques and Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Computer science; Natural language processing; XML; Artificial intelligence; Information retrieval; World Wide Web","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"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":[0.0001275568,0.0002467189,0.0002354927,0.0001447893,0.000097631,0.0001340449,0.002605152,0.0001436208,0.002261932],"category_scores_gemma":[0.00003333217,0.000246998,0.00008470257,0.000275027,0.00003564744,0.000479612,0.001260275,0.0002952476,0.1281047],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007265691,"about_ca_system_score_gemma":0.0001362422,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002427138,"about_ca_topic_score_gemma":0.000005153525,"domain_scores_codex":[0.9983401,0.00003072989,0.000288918,0.0006357512,0.0004315267,0.0002730311],"domain_scores_gemma":[0.9972435,0.00009148916,0.0002226799,0.002251727,0.00008702193,0.0001036195],"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":[0.000001051657,0.00004070195,1.907703e-7,0.00002240577,0.00001675488,0.00001089459,0.000003735274,0.00004588102,0.000004276319,0.006327446,0.9924517,0.001074985],"study_design_scores_gemma":[0.000137097,0.00002904874,0.00000258924,0.0000266828,0.00001503443,0.000009949927,0.000002114226,0.001154837,0.00002296275,0.002883842,0.9954405,0.0002753407],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[1.299918e-7,6.107194e-7,0.2617708,0.0000346653,0.0003221391,0.0002795369,0.7373064,0.0001187023,0.000167112],"genre_scores_gemma":[0.000001640392,0.0001725633,0.06181538,0.0008637624,0.0001308713,0.00009881909,0.9366354,0.00001076132,0.0002707921],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1999554,"threshold_uncertainty_score":0.9999982,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02406290567614974,"score_gpt":0.292643015888422,"score_spread":0.2685801102122723,"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."}}