{"id":"W2013343793","doi":"10.1006/jnca.2000.0107","title":"Power LAN MIB for management of intelligent telecommunication equipment","year":2000,"lang":"en","type":"article","venue":"Journal of Network and Computer Applications","topic":"Mobile Agent-Based Network Management","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"University of British Columbia","keywords":"Simple Network Management Protocol; Computer science; Computer network; Network management; Network management application; Network management station; Power management; Network monitoring; Protocol (science); Telecommunications; Power (physics); Network architecture","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004246983,0.0004329195,0.0002736846,0.0008503493,0.0005464824,0.0008015495,0.0009008641,0.0003340667,0.05434617],"category_scores_gemma":[0.0005317919,0.000176395,0.0001215061,0.0004855717,0.000149885,0.0008535828,0.0006169454,0.000743839,0.01357807],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000453348,"about_ca_system_score_gemma":0.0003613962,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009695911,"about_ca_topic_score_gemma":0.001279891,"domain_scores_codex":[0.9997908,0.00004201144,0.00001054294,0.00002644643,0.00009285504,0.00003735097],"domain_scores_gemma":[0.999729,0.00003832723,0.00002166751,0.00006318815,0.0001105606,0.0000372524],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.002039545,0.0004415573,0.00346979,0.0005409964,0.00005516927,0.0006931946,0.0003898305,0.002278399,0.129267,0.03335275,0.1858341,0.6416377],"study_design_scores_gemma":[0.0003504788,0.0009155154,0.007726525,0.0001487652,0.0001273914,0.0009608308,0.0001684156,0.07367167,0.1501329,0.005826491,0.759907,0.00006397434],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1314905,0.003487174,0.3950244,0.002042335,0.001146408,0.00181402,0.003372464,0.07057357,0.3910492],"genre_scores_gemma":[0.5617712,0.00101281,0.06843037,0.0009008548,0.0004116762,0.0008020257,0.004773677,0.001794775,0.3601026],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.05434617,"threshold_uncertainty_score":0.1818061,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01318004453435967,"score_gpt":0.2517658293708749,"score_spread":0.2385857848365153,"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."}}