{"id":"W4398560446","doi":"10.7910/dvn/pkjufn/j88eon","title":"FCC2001.287.ran","year":2020,"lang":"en","type":"dataset","venue":"Harvard Dataverse","topic":"ICT Impact and Policies","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Natural Resources Canada","funders":"","keywords":"Ran; Computer science; Computer network","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00006060771,0.0003942384,0.000386561,0.0001371678,0.0000566066,0.0001090778,0.0006265846,0.0002826691,0.0169343],"category_scores_gemma":[0.00008105683,0.0004050272,0.0001174304,0.0001699472,0.00004562065,0.0001989435,0.000170678,0.0005243164,0.4612997],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006602565,"about_ca_system_score_gemma":0.00004397836,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002109289,"about_ca_topic_score_gemma":0.00006255356,"domain_scores_codex":[0.9989297,0.00002241526,0.0002503971,0.000128093,0.0002347096,0.0004347065],"domain_scores_gemma":[0.9987509,0.00004797761,0.00004388466,0.0008963363,0.00001641715,0.0002445144],"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":[0.000007888279,0.000009246195,6.860766e-7,0.0002622352,0.00009263963,0.00004383923,0.0001476378,0.000121034,0.00003881306,0.000008947614,0.9991438,0.0001231734],"study_design_scores_gemma":[0.0002081517,0.00002458663,0.00001158986,0.00005025769,0.0001075496,0.00001534,0.0000848585,0.00008889233,0.00006807195,0.0000049575,0.9988984,0.0004373709],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00002457964,0.000003071331,0.00001785685,0.000006669353,0.00129729,0.0001434648,0.9967575,0.0003547785,0.001394775],"genre_scores_gemma":[0.00002566807,0.0008142598,0.00003796026,0.0005700287,0.0008939832,0.00001104538,0.9973376,0.00005776048,0.0002517168],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.4443654,"threshold_uncertainty_score":0.9998401,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01491807828707306,"score_gpt":0.2285909978164777,"score_spread":0.2136729195294046,"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."}}