{"id":"W4398711895","doi":"10.7910/dvn/pkjufn/bn8zo9","title":"FCC2002.331.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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0009577117,0.003334458,0.001627591,0.003716239,0.001126955,0.003278541,0.003841816,0.002998738,0.08524214],"category_scores_gemma":[0.005277954,0.0007474697,0.001715897,0.006912936,0.0005189914,0.001789232,0.001987041,0.001700436,0.1544783],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001762536,"about_ca_system_score_gemma":0.00222147,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04507995,"about_ca_topic_score_gemma":0.07282247,"domain_scores_codex":[0.9988702,0.0001669013,0.0001168649,0.000321521,0.0002441827,0.0002803485],"domain_scores_gemma":[0.9978818,0.0003984232,0.0001724451,0.0006262514,0.0006466263,0.0002743629],"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":[0.00004720909,0.00001170708,0.0002691603,0.0002632466,0.00001457973,0.00001051122,0.000007490135,0.0002283772,0.00005147303,0.000247403,0.9977549,0.001094053],"study_design_scores_gemma":[0.0003251077,0.00003293287,0.002989608,0.0002837401,0.00003156245,0.00005739128,0.00007813539,0.001079336,0.0003769707,0.001483395,0.9932254,0.00003636899],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00008438859,0.00005454115,0.00003543939,0.00005750319,0.00003098977,0.000005652588,0.9984772,0.0004530285,0.0008012024],"genre_scores_gemma":[0.0003046724,0.00003848856,0.0001093259,0.00004184971,0.000009517841,0.00002080841,0.9989564,0.00006505573,0.0004537301],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.9147578,"threshold_uncertainty_score":0.2851633,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01187632136744047,"score_gpt":0.1983757581922939,"score_spread":0.1864994368248535,"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."}}