{"id":"W6930373419","doi":"10.5281/zenodo.10608441","title":"LENS: A LEO Satellite Network Measurement Dataset - 202311 - Part 1","year":2024,"lang":"en","type":"dataset","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Bioenergy crop production and management","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"","keywords":"Satellite; Field (mathematics); Data collection; Measure (data warehouse); Data processing","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":[],"consensus_categories":[],"category_scores_codex":[0.0008339774,0.002295471,0.001251785,0.002740138,0.0006924216,0.001621998,0.00247827,0.001955173,0.04836664],"category_scores_gemma":[0.004042441,0.0005590701,0.001251862,0.005617609,0.0003723698,0.001585025,0.001659082,0.001496882,0.08390991],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001553736,"about_ca_system_score_gemma":0.001715479,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03491047,"about_ca_topic_score_gemma":0.05553668,"domain_scores_codex":[0.9989777,0.0001783894,0.0001150771,0.0002948941,0.0002735673,0.0001604441],"domain_scores_gemma":[0.9985454,0.0002612243,0.0001244943,0.0003917613,0.0005489464,0.0001281288],"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":[0.00004193008,0.00001764241,0.0007036382,0.0002614517,0.00003129442,0.00001592717,0.00001058806,0.0005500955,0.0001464732,0.0003710377,0.9958039,0.002046037],"study_design_scores_gemma":[0.00023821,0.00002666372,0.007123931,0.0001790255,0.00004083412,0.00007631336,0.00009372481,0.002243515,0.0006644085,0.002222709,0.9870356,0.00005504524],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0002184178,0.00005771237,0.0001271494,0.00005647975,0.0000244487,0.0000110557,0.9983128,0.0006159127,0.0005760665],"genre_scores_gemma":[0.0004055557,0.00002540988,0.0002398173,0.000029064,0.000006766446,0.00003362989,0.9987738,0.00009175258,0.000394161],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.04836664,"threshold_uncertainty_score":0.1618025,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08489923960104055,"score_gpt":0.2347183994532963,"score_spread":0.1498191598522557,"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."}}