{"id":"W6958997318","doi":"10.7281/t1/bmathh/7ft2bh","title":"13_B2.tar.009","year":2021,"lang":"en","type":"dataset","venue":"Research Data Repository, Duke University","topic":"Legal and Regulatory Analysis","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Prince Edward Island","funders":"","keywords":"Process (computing); Compression (physics); Object (grammar)","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":["insufficient_payload"],"category_scores_codex":[0.001281877,0.001798261,0.001289662,0.003914344,0.001220693,0.00332045,0.003076753,0.002091929,0.4944486],"category_scores_gemma":[0.007835859,0.001051737,0.001255237,0.007209822,0.0005289834,0.001769917,0.002390849,0.001775752,0.4562534],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001816017,"about_ca_system_score_gemma":0.00282766,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03467542,"about_ca_topic_score_gemma":0.04651129,"domain_scores_codex":[0.9988182,0.0001828771,0.0001489836,0.0003225174,0.0002569909,0.000270446],"domain_scores_gemma":[0.9963444,0.0010343,0.0002732831,0.0008497079,0.001071339,0.0004270143],"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":[0.00003541786,0.0000125848,0.0001824339,0.0001468283,0.00000575399,0.000006357082,0.000009040201,0.00005605231,0.00004488554,0.0002391448,0.9985511,0.0007103356],"study_design_scores_gemma":[0.0003238972,0.00002080164,0.003082816,0.0001906212,0.00001626501,0.00003437052,0.00009141998,0.0002662865,0.0003890232,0.001411419,0.994145,0.00002819692],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0000346154,0.000006478758,0.00003323443,0.00003892931,0.00001186395,0.00000880502,0.9988371,0.0002607507,0.0007683356],"genre_scores_gemma":[0.0002373006,0.00001548281,0.0001552569,0.00004207409,0.000009709756,0.00006834576,0.9976453,0.0002230115,0.00160354],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.5055515,"threshold_uncertainty_score":0.7211077,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1861045416920744,"score_gpt":0.4232840275051712,"score_spread":0.2371794858130969,"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."}}