{"id":"W4398563546","doi":"10.7910/dvn/pkjufn/oci1tx","title":"FCC2002.045.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":[0.0009852124,0.003153811,0.001583259,0.003653191,0.001032745,0.003008435,0.003661867,0.002892565,0.0846725],"category_scores_gemma":[0.005483418,0.0007172829,0.001681737,0.006403632,0.0005261372,0.001714403,0.001927817,0.001671546,0.1443844],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001629593,"about_ca_system_score_gemma":0.002223033,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04152077,"about_ca_topic_score_gemma":0.06606072,"domain_scores_codex":[0.9989028,0.0001632666,0.0001123707,0.000315146,0.0002422781,0.0002640519],"domain_scores_gemma":[0.9978588,0.0003997488,0.0001746986,0.0006412412,0.0006382395,0.0002872168],"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":[0.00004823267,0.00001150846,0.000276972,0.0002330071,0.00001448164,0.000009825009,0.000006797186,0.0002392905,0.00004809253,0.0002191343,0.997813,0.001079599],"study_design_scores_gemma":[0.0003933283,0.000038418,0.003515646,0.0002768876,0.00003599876,0.00006155829,0.00008343401,0.001274944,0.0004013378,0.001668395,0.9922097,0.0000403364],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00009006935,0.00005021133,0.0000356543,0.00006325981,0.00003336,0.000006021267,0.9986156,0.0004226803,0.0006830437],"genre_scores_gemma":[0.0003427908,0.00003889861,0.0001143519,0.00004397839,0.00001151049,0.00002352844,0.9988844,0.00006318049,0.0004774829],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.9153275,"threshold_uncertainty_score":0.2832578,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01186855000602602,"score_gpt":0.1982685848667247,"score_spread":0.1864000348606986,"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."}}