{"id":"W4398620088","doi":"10.7910/dvn/bh43df/qd2fas","title":"map_vpd_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":"XML; Element (criminal law); Computer science; Geography; 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":[0.00154421,0.003460254,0.001723657,0.00639682,0.001316955,0.004315161,0.004021355,0.002862616,0.1661263],"category_scores_gemma":[0.009629777,0.001315514,0.001596084,0.008686594,0.0008312097,0.003166817,0.00374383,0.002353882,0.2085461],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002003587,"about_ca_system_score_gemma":0.003059445,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02473045,"about_ca_topic_score_gemma":0.03542137,"domain_scores_codex":[0.99844,0.0002853533,0.0001987576,0.000464344,0.0003519378,0.0002595759],"domain_scores_gemma":[0.9965656,0.000961652,0.0002206642,0.001117437,0.0008080156,0.0003267251],"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":[0.00004005764,0.00001244129,0.0002536458,0.0005349565,0.00002487974,0.00001293769,0.00003297919,0.000140028,0.0001309768,0.0006631826,0.9967436,0.001410267],"study_design_scores_gemma":[0.0001386801,0.0000129385,0.001177303,0.0002360003,0.00002178345,0.00004208659,0.00008672912,0.0002844037,0.0005610494,0.00162121,0.9957874,0.0000303064],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00008254128,0.00004870206,0.0001018867,0.00008239524,0.00003232003,0.00001034186,0.9971871,0.001368385,0.001086317],"genre_scores_gemma":[0.0003031558,0.00005456942,0.00030914,0.00005131013,0.000007500072,0.00004872245,0.9981729,0.0003877109,0.0006649853],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8338737,"threshold_uncertainty_score":0.5557479,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02680334605394013,"score_gpt":0.2706383758113485,"score_spread":0.2438350297574084,"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."}}