{"id":"W4398539165","doi":"10.7910/dvn/pkjufn/u9oyrl","title":"FCC2001.061.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":[0.00006107664,0.0004478355,0.0004849223,0.00009727634,0.00006224393,0.0001088386,0.000670386,0.0003681516,0.01706333],"category_scores_gemma":[0.0000415227,0.0004726962,0.0001387709,0.0001915914,0.00004593407,0.0001680612,0.0001970568,0.0007385847,0.335486],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006867757,"about_ca_system_score_gemma":0.00002726787,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007884853,"about_ca_topic_score_gemma":0.00007001918,"domain_scores_codex":[0.998509,0.00002789378,0.000331787,0.0003984492,0.0002792858,0.0004535386],"domain_scores_gemma":[0.9985402,0.00004635141,0.00005846494,0.001069256,0.00002277977,0.0002629489],"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":[0.00001015214,0.00001400948,4.272817e-7,0.000243366,0.0001054963,0.000219516,0.000009793099,0.002664561,0.00001852292,0.000005236479,0.9962546,0.000454379],"study_design_scores_gemma":[0.0002632705,0.0000219437,0.000004478089,0.00008503127,0.0001048438,0.0000129021,0.00001566815,0.003308492,0.00002564389,0.000003732489,0.9956373,0.0005167125],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.000007785722,0.000006019961,0.00006488156,0.000004287828,0.001826151,0.0001786236,0.9967725,0.0003698204,0.000769971],"genre_scores_gemma":[0.00004008901,0.002065905,0.0001683696,0.0002948749,0.00143886,0.00001337107,0.9957809,0.00007915145,0.0001184743],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.3184227,"threshold_uncertainty_score":0.9997725,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0118495727525685,"score_gpt":0.1999503156488169,"score_spread":0.1881007428962485,"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."}}