{"id":"W4398584401","doi":"10.7910/dvn/pkjufn/twwyjx","title":"FCC2001.032.ran","year":2020,"lang":"en","type":"dataset","venue":"Harvard Dataverse","topic":"Wireless Sensor Networks and IoT","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":[0.00006187477,0.0004482177,0.00048777,0.00009784837,0.00006216237,0.0001120595,0.0006721441,0.000368897,0.01573717],"category_scores_gemma":[0.0000414519,0.0004726772,0.0001385826,0.0001918344,0.0000463773,0.0001696085,0.0001972602,0.0007393084,0.3277467],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006946145,"about_ca_system_score_gemma":0.00002733444,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007520342,"about_ca_topic_score_gemma":0.00006553506,"domain_scores_codex":[0.9985044,0.00002797101,0.0003330536,0.0003991518,0.000280937,0.0004544583],"domain_scores_gemma":[0.9985406,0.00004686961,0.0000590189,0.001070606,0.00002285754,0.0002600256],"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":[0.00001032959,0.00001398427,4.444547e-7,0.0002450678,0.000104905,0.0002232117,0.000009676038,0.00260851,0.00002104406,0.000007054117,0.9963626,0.0003932081],"study_design_scores_gemma":[0.0002642514,0.00002205886,0.000004908568,0.00008700094,0.0001036695,0.00001294038,0.000015226,0.0036878,0.00002146693,0.000003720114,0.9952602,0.000516698],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.000007309676,0.000005858606,0.00008419027,0.000004222487,0.001780619,0.0001784727,0.9967831,0.0003705035,0.0007857468],"genre_scores_gemma":[0.00003381635,0.001915546,0.0001704244,0.0003022054,0.001445986,0.0000133866,0.9959177,0.00007916179,0.0001217639],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.3120095,"threshold_uncertainty_score":0.9997725,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01185332379072606,"score_gpt":0.2000363718957978,"score_spread":0.1881830481050718,"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."}}