{"id":"W4398662437","doi":"10.7910/dvn/itvlik/fv9uwq","title":"gde-1-1-15.zip","year":2020,"lang":"zh","type":"dataset","venue":"Harvard Dataverse","topic":"Algorithms and Data Compression","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Zip code; Computer science; Database","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":[0.001245502,0.003174998,0.001734452,0.003779962,0.001019283,0.003325463,0.004615347,0.002529181,0.2258411],"category_scores_gemma":[0.006860138,0.0008996543,0.001198349,0.006498618,0.0007156108,0.00249239,0.002862629,0.001860371,0.3061636],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00178326,"about_ca_system_score_gemma":0.00179157,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0102828,"about_ca_topic_score_gemma":0.01594904,"domain_scores_codex":[0.9988236,0.0001404864,0.000111538,0.0003164168,0.0003193082,0.000288625],"domain_scores_gemma":[0.9973006,0.0004634528,0.0001543967,0.001082076,0.0006821586,0.0003173025],"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":[0.00005105147,0.00001956226,0.0001604228,0.0002283963,0.00000855986,0.000006051546,0.000008322994,0.000125474,0.0001059682,0.0003487607,0.9967704,0.00216715],"study_design_scores_gemma":[0.0004983461,0.00005839091,0.001684018,0.0001832933,0.00001315186,0.00005637409,0.00006401334,0.001027839,0.001218444,0.002546484,0.9926229,0.00002667671],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0002286714,0.00007851514,0.0001472172,0.0001349486,0.0000654213,0.00002915791,0.9941266,0.003077769,0.002111796],"genre_scores_gemma":[0.0006313249,0.00006294646,0.0004546517,0.00008465914,0.00001823821,0.00007331069,0.9969143,0.0004555141,0.001305056],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.7741588,"threshold_uncertainty_score":0.7555138,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02274588612559614,"score_gpt":0.2446866848740564,"score_spread":0.2219407987484602,"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."}}