{"id":"W4398269241","doi":"10.7910/dvn/dnw5rw/k9fs4h","title":"manifest.xml","year":2019,"lang":"en","type":"dataset","venue":"Harvard Dataverse","topic":"Computability, Logic, AI Algorithms","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"XML; Computer science; Information retrieval; Programming language; 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","open_science","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0007017152,0.0006688634,0.0007319486,0.0003396122,0.0001487855,0.0006224919,0.007180443,0.0004721247,0.008554128],"category_scores_gemma":[0.0002391047,0.0006582764,0.0002664175,0.0005031467,0.0001219549,0.000997989,0.006011276,0.0008533531,0.4282399],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002322187,"about_ca_system_score_gemma":0.0003874766,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003463725,"about_ca_topic_score_gemma":0.00007436918,"domain_scores_codex":[0.9956057,0.0002359114,0.0006086139,0.001789736,0.0009691715,0.0007908514],"domain_scores_gemma":[0.9913309,0.000301491,0.0003580697,0.007561368,0.0001606469,0.000287566],"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":[0.000005545872,0.0001505298,0.000006486479,0.0001447798,0.0000481742,0.0003051316,0.00001788369,0.00003981709,0.000002384188,0.0003772744,0.9971918,0.001710153],"study_design_scores_gemma":[0.0003921993,0.0001152295,0.00008883012,0.00005604757,0.00004899899,0.0001331524,0.000006423653,0.003770418,0.000008820158,0.0003767595,0.9942576,0.0007454774],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.000004295472,0.00000300106,0.02331182,0.00002761544,0.004900796,0.0005940675,0.9704279,0.0002673055,0.000463225],"genre_scores_gemma":[0.000005146323,0.0001072552,0.01460785,0.00079226,0.0005302125,0.0000267889,0.9833023,0.00002723863,0.000600939],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.4196858,"threshold_uncertainty_score":0.9995868,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0237808301180951,"score_gpt":0.2497431778568876,"score_spread":0.2259623477387925,"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."}}