{"id":"W4394518783","doi":"10.6084/m9.figshare.3511898","title":"Appendix C. A table showing descriptive statistics of landscape-scale variables around bog ponds (N=70 ponds) sampled within mined peatlands in eastern New Brunswick, Canada.","year":2016,"lang":"en","type":"dataset","venue":"Figshare","topic":"Peatlands and Wetlands Ecology","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Bog; Peat; Table (database); Scale (ratio); Physical geography; Hydrology (agriculture); Geography; Environmental science; Descriptive statistics; Forestry; Archaeology; Statistics; Geology; Cartography; Mathematics; Computer science; Database; Geotechnical engineering","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.001110239,0.001223825,0.001137226,0.004670094,0.00138443,0.0019296,0.002212394,0.0008279408,0.1809557],"category_scores_gemma":[0.00844466,0.0008041752,0.0008053443,0.01273259,0.0004505511,0.0008516025,0.001383134,0.001051348,0.06926646],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.007827682,"about_ca_system_score_gemma":0.01709173,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8156511,"about_ca_topic_score_gemma":0.9096991,"domain_scores_codex":[0.9991203,0.00005554935,0.0001268075,0.0001919067,0.0002838649,0.0002215352],"domain_scores_gemma":[0.9896982,0.001779686,0.0006941777,0.0008115217,0.006271436,0.0007449207],"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":[0.0000236891,0.00001113719,0.003656472,0.0004383648,0.0000156803,0.00001309295,0.00002905906,0.0001873279,0.0000297322,0.000200336,0.9938194,0.001575837],"study_design_scores_gemma":[0.0002345484,0.000009970077,0.04937137,0.0007754011,0.00004439472,0.00004571641,0.0003176733,0.0003263336,0.0001844828,0.0006424133,0.9480047,0.00004298097],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004644362,0.000008071662,0.00001417162,0.000008509728,0.000002817446,0.000007310562,0.9996498,0.00002015737,0.0002426725],"genre_scores_gemma":[0.0005444249,0.00002946386,0.0001930805,0.00002046133,0.000002384599,0.00009153599,0.9980596,0.0000303863,0.001028749],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1843489,"threshold_uncertainty_score":0.605357,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02154377029179607,"score_gpt":0.2262212651675143,"score_spread":0.2046774948757182,"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."}}