{"id":"W4398409165","doi":"10.7910/dvn/pkjufn/ydxe8t","title":"FCC2001.323.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":[0.00006184771,0.0004488664,0.0004883517,0.00009793435,0.00006250123,0.0001123272,0.000672943,0.0003693525,0.01575601],"category_scores_gemma":[0.0000418011,0.0004735756,0.000139817,0.000189741,0.00004674218,0.0001693083,0.0001975417,0.0007413414,0.3239877],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007279495,"about_ca_system_score_gemma":0.00002813922,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007824336,"about_ca_topic_score_gemma":0.00006896919,"domain_scores_codex":[0.9985045,0.00002803143,0.0003320948,0.0003995245,0.0002805367,0.0004553651],"domain_scores_gemma":[0.9985394,0.00004667477,0.00005886136,0.001071873,0.00002270075,0.0002604574],"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":[0.00001034616,0.00001360328,4.123367e-7,0.0002448951,0.0001049854,0.0002267206,0.000009735779,0.002948233,0.00002050183,0.000007181861,0.9960274,0.000386025],"study_design_scores_gemma":[0.0002655653,0.00002266424,0.000004526391,0.00008767124,0.0001036717,0.00001328494,0.00001562799,0.003820386,0.00002114982,0.000003918638,0.9951242,0.0005173507],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.000006940396,0.000006117471,0.00008665267,0.000004231175,0.001796424,0.0001787848,0.9967306,0.0003718738,0.0008183295],"genre_scores_gemma":[0.00003557314,0.001995559,0.0001729039,0.0002999584,0.00143635,0.00001337184,0.9958505,0.00007933047,0.0001164623],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.3082317,"threshold_uncertainty_score":0.9997716,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01184558204832753,"score_gpt":0.1998632451143943,"score_spread":0.1880176630660668,"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."}}