{"id":"W4398543435","doi":"10.7910/dvn/pkjufn/cmzupm","title":"FCC2001.222.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":[0.0000616485,0.0004481417,0.00048599,0.00009766601,0.000062365,0.0001120759,0.0006713541,0.0003687121,0.01568111],"category_scores_gemma":[0.00004102498,0.0004729941,0.0001396199,0.0001891203,0.00004650215,0.0001699926,0.0001906997,0.0007394179,0.3278509],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006973834,"about_ca_system_score_gemma":0.00002724786,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008039309,"about_ca_topic_score_gemma":0.00006901434,"domain_scores_codex":[0.9985077,0.00002782493,0.0003312608,0.0003987132,0.0002800499,0.0004544939],"domain_scores_gemma":[0.9985422,0.00004715737,0.00005850348,0.001069403,0.00002267855,0.0002599963],"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":[0.00001011115,0.000013999,6.151031e-7,0.0002428958,0.0001044901,0.0002236075,0.000009911862,0.002833491,0.00002020805,0.000007132978,0.9961176,0.0004159625],"study_design_scores_gemma":[0.0002646238,0.00001864322,0.000006355359,0.00008560699,0.0001034972,0.00001323184,0.00001576799,0.00357319,0.00002156084,0.000003738432,0.9953776,0.0005161907],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.000007794494,0.000006403985,0.00008477555,0.000004720101,0.001757502,0.0001783377,0.9968188,0.0003800033,0.0007616447],"genre_scores_gemma":[0.00004205899,0.001955142,0.0001753512,0.0003043066,0.001426344,0.00001306976,0.9959124,0.00008047668,0.00009090032],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.3121698,"threshold_uncertainty_score":0.9997722,"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."}}