{"id":"W4398688943","doi":"10.7910/dvn/pkjufn/3s1qni","title":"FCC2003.333.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":[0.00006088537,0.0004480402,0.0004855002,0.00009620268,0.00006242813,0.0001155404,0.0006642431,0.0003686015,0.01569592],"category_scores_gemma":[0.00004710888,0.0004729898,0.0001319644,0.0002085845,0.00004661702,0.0001700939,0.0001915797,0.0007375837,0.3238204],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007244789,"about_ca_system_score_gemma":0.0000312279,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000727392,"about_ca_topic_score_gemma":0.0000631199,"domain_scores_codex":[0.9985171,0.00002874157,0.0003300257,0.0003984033,0.0002785056,0.0004472226],"domain_scores_gemma":[0.9985479,0.00004277276,0.00005860755,0.001068422,0.00002543977,0.0002568639],"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":[0.000009879356,0.0000132636,3.420298e-7,0.000244874,0.0001047254,0.0002804148,0.000009864946,0.002462791,0.0000186211,0.000008973823,0.9965065,0.0003397166],"study_design_scores_gemma":[0.0002595638,0.0000218814,0.000004127594,0.0000847349,0.0001035018,0.0000174479,0.00001545738,0.003489306,0.00002028563,0.000003513825,0.9954635,0.0005167074],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.000006102642,0.000006258653,0.0001002606,0.000003741571,0.001830643,0.0001805178,0.9967062,0.0003616943,0.000804571],"genre_scores_gemma":[0.00003711387,0.001865107,0.0001939461,0.0003072021,0.00134557,0.00001347898,0.9960434,0.00007912501,0.0001150213],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.3081245,"threshold_uncertainty_score":0.9997722,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01230371519253367,"score_gpt":0.2021096751504535,"score_spread":0.1898059599579199,"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."}}