{"id":"W6960891967","doi":"10.1371/journal.pone.0113511.t002","title":"Summary of the differences in connectivity measures of Canada lynx occurrence and pseudo-absences in Ontario, Canada; all &lt;i&gt;t&lt;/i&gt;-tests were one-sided with p-values&lt;0.05 in bold and p-values&lt;0.1 in italics.","year":2015,"lang":"en","type":"dataset","venue":"Figshare","topic":"Wheat and Barley Genetics and Pathology","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Habitat; Land cover; Cover (algebra); Measure (data warehouse); Wildlife corridor; Forest cover; Vegetation cover","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":[0.0004782797,0.000426231,0.000529126,0.001474787,0.00100599,0.0006920439,0.001045625,0.0002821161,0.0121431],"category_scores_gemma":[0.002727865,0.0002277313,0.0006973054,0.003142364,0.0005327033,0.0005215327,0.0007797687,0.0006078604,0.0007284699],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01041032,"about_ca_system_score_gemma":0.01558837,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9905459,"about_ca_topic_score_gemma":0.9956685,"domain_scores_codex":[0.9993531,0.00003837777,0.00005466182,0.0001662716,0.0002334106,0.0001542058],"domain_scores_gemma":[0.9969728,0.0003774442,0.0006319102,0.0001031629,0.001385765,0.0005289451],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004005329,0.00002620912,0.9059382,0.0004208287,0.0006434848,0.0002065567,0.001284957,0.001245951,0.001496392,0.001126476,0.06733537,0.01987517],"study_design_scores_gemma":[0.000005827887,0.00001017051,0.9944105,0.00002628334,0.00004331234,0.00002878614,0.0008419666,0.0002482369,0.00004601403,0.00003360367,0.004295209,0.00001006118],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"dataset","genre_scores_codex":[0.5924428,0.002575182,0.001247592,0.00119047,0.0001825407,0.0001275156,0.3701148,0.0002936362,0.03182543],"genre_scores_gemma":[0.9154068,0.0009473888,0.0009498378,0.0001341378,0.00003016377,0.00009523317,0.06644928,0.00008646273,0.01590087],"genre_candidate":"dataset","genre_consensus":null,"teacher_disagreement_score":0.0121431,"threshold_uncertainty_score":0.07553256,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04994950898213203,"score_gpt":0.2203747432379006,"score_spread":0.1704252342557686,"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."}}