{"id":"W4398567113","doi":"10.7910/dvn/66hucd/3ehyee","title":"map_element.xml","year":2019,"lang":"en","type":"dataset","venue":"Harvard Dataverse","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Computer science; Element (criminal law); XML; Database; Information retrieval; 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":[0.001722095,0.00409594,0.00193957,0.007143155,0.00140963,0.004946786,0.004438587,0.003240989,0.2345619],"category_scores_gemma":[0.009759639,0.001600191,0.001773189,0.009521851,0.0008217581,0.004472463,0.00450887,0.002577369,0.3102595],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00202355,"about_ca_system_score_gemma":0.003002634,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01824059,"about_ca_topic_score_gemma":0.02363839,"domain_scores_codex":[0.9981282,0.0003361468,0.0002279017,0.0006371685,0.0003916984,0.0002789212],"domain_scores_gemma":[0.9963684,0.0009454577,0.0002129707,0.001321702,0.0007951512,0.0003562873],"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":[0.00005038589,0.00001539698,0.0002487148,0.0005493817,0.00002855634,0.00001361805,0.00003433483,0.0001324305,0.0001672128,0.0006882115,0.9962954,0.001776379],"study_design_scores_gemma":[0.0001452371,0.00001754814,0.001121095,0.0001995489,0.00002264734,0.00004790219,0.00008217204,0.0003166007,0.0006884079,0.001812149,0.9955135,0.00003327871],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00007867117,0.00004497286,0.0001378405,0.00009220874,0.00003936769,0.00001323275,0.9958171,0.002410328,0.001366304],"genre_scores_gemma":[0.0003370921,0.00005511128,0.0003335893,0.00006613618,0.00001020855,0.00005230655,0.9976549,0.0006613285,0.0008292185],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.7654381,"threshold_uncertainty_score":0.7846876,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02688939753593304,"score_gpt":0.2710814908654181,"score_spread":0.244192093329485,"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."}}