{"id":"W4398755020","doi":"10.7910/dvn/dnw5rw/wxa6fm","title":"map_vpd_element.xml","year":2019,"lang":"en","type":"dataset","venue":"Harvard Dataverse","topic":"Image Processing and 3D Reconstruction","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"XML; Element (criminal law); Computer science; Information retrieval; Database; Physics; World Wide Web; Political science","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001000146,0.004475645,0.002051811,0.005407738,0.001182309,0.003887565,0.004904635,0.003281506,0.131757],"category_scores_gemma":[0.00536254,0.001335241,0.001824659,0.007452636,0.0007325396,0.002670639,0.003808736,0.002264132,0.2129215],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001593049,"about_ca_system_score_gemma":0.002258578,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01535522,"about_ca_topic_score_gemma":0.02132315,"domain_scores_codex":[0.9987306,0.0001570954,0.0001599297,0.0003966359,0.0003074461,0.0002483035],"domain_scores_gemma":[0.9981683,0.0004104686,0.00013307,0.0006354738,0.0004566703,0.0001960009],"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":[0.00005934337,0.00001846976,0.0002553187,0.0006770965,0.00002228337,0.00001785737,0.00002759949,0.0001803446,0.000206918,0.0005282217,0.9955771,0.002429456],"study_design_scores_gemma":[0.0001626708,0.00001696438,0.001128892,0.0002233596,0.00002134089,0.00006835896,0.00007786755,0.0004805798,0.0009580983,0.001639224,0.9951893,0.00003335997],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001025726,0.00007184276,0.0001794361,0.00005917689,0.0000293451,0.00001584679,0.9959468,0.002537056,0.001057987],"genre_scores_gemma":[0.0003094668,0.00006949816,0.0004986178,0.0000399649,0.000006798527,0.00006573094,0.9980422,0.0003989913,0.000568716],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.868243,"threshold_uncertainty_score":0.440771,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01535788024428074,"score_gpt":0.2406205006661064,"score_spread":0.2252626204218257,"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."}}