{"id":"W2967394175","doi":"10.19189/map.2018.jsp.368","title":"Application of terrestrial laser scanning to quantify surface changes in restored and degraded blanket bogs","year":2019,"lang":"en","type":"article","venue":"Mires and Peat","topic":"Remote Sensing and LiDAR Applications","field":"Environmental Science","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Trent University; Diputación Foral de Bizkaia; Nottingham Trent University","keywords":"Blanket; Bog; Environmental science; Sphagnum; Hydrology (agriculture); Geology; Remote sensing; Ecology; Geography; Peat; Biology; Geotechnical engineering; Archaeology","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009878457,0.00005377491,0.00008622303,0.0000199621,0.00003018821,0.00001300801,0.00004304668,0.00003258837,0.00001529931],"category_scores_gemma":[0.000005368318,0.00004768456,0.000007892011,0.0001013946,0.00004213728,0.00002536112,0.00004251037,0.00003449558,0.00001951574],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001388599,"about_ca_system_score_gemma":0.000002071401,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005577976,"about_ca_topic_score_gemma":0.001929841,"domain_scores_codex":[0.9995641,0.00001903756,0.00007776081,0.0001753002,0.00007408404,0.00008968102],"domain_scores_gemma":[0.999768,0.00003156769,0.00002793022,0.0001296772,0.000001642728,0.00004118809],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00008575647,0.00003551021,0.6650142,0.00001792455,0.00000415655,7.377746e-7,0.002405268,0.0009637594,0.2891046,0.00005236641,0.001010202,0.04130549],"study_design_scores_gemma":[0.0004090691,0.00006660663,0.9614937,0.00002850632,0.00000542321,0.000002803107,0.0002616974,0.006631369,0.009220434,0.00007746477,0.02168737,0.0001155782],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.998118,0.00004154215,0.00004723021,0.0007825881,0.00002026634,0.0002107238,0.00000282421,0.000008156709,0.0007686449],"genre_scores_gemma":[0.998852,0.00002267024,0.0007676207,0.00004632242,0.00001373076,0.000001617839,0.000005530445,0.000004670551,0.0002858324],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2964795,"threshold_uncertainty_score":0.8432269,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01446092692096641,"score_gpt":0.2487983535663378,"score_spread":0.2343374266453714,"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."}}