{"id":"W4392510916","doi":"10.1016/j.mex.2024.102641","title":"An inexpensive artificial snake hibernaculum built using readily available plumbing supplies","year":2024,"lang":"en","type":"article","venue":"MethodsX","topic":"Amphibian and Reptile Biology","field":"Environmental Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Windsor; Laurentian University; World Wildlife Fund Canada","funders":"Employment and Social Development Canada; Natural Sciences and Engineering Research Council of Canada; Ministère de l’Environnement, de la Protection de la nature et des Parcs; Nature Conservancy of Canada; Environment and Climate Change Canada; Government of Ontario; Ontario Ministry of Natural Resources and Forestry; Ministry of Natural Resources","keywords":"Environmental science; Microclimate; Ecology; Hydrology (agriculture); Geotechnical engineering; Biology; Engineering","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0001516444,0.0005863064,0.0003367166,0.0004789629,0.0002632838,0.0002938235,0.0009380909,0.0004093748,0.01108077],"category_scores_gemma":[0.0003219122,0.0003935274,0.0004879252,0.0001929201,0.0001414514,0.0004602967,0.0007152989,0.0003591899,0.002295227],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001265524,"about_ca_system_score_gemma":0.0002591931,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003812098,"about_ca_topic_score_gemma":0.0008906501,"domain_scores_codex":[0.99983,0.00001944403,0.00001481999,0.00005062293,0.00006186648,0.00002328098],"domain_scores_gemma":[0.9997309,0.00003296573,0.00005192573,0.00004928697,0.00005863006,0.00007625755],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0006389467,0.0005945582,0.01524889,0.001228857,0.00008690001,0.001175194,0.0004075457,0.004571767,0.7632609,0.001276809,0.006155127,0.2053546],"study_design_scores_gemma":[0.0005858682,0.01318679,0.2042572,0.0005359126,0.0007888645,0.01339393,0.0005945883,0.07059203,0.4297448,0.001603369,0.264336,0.0003807423],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.704483,0.0005171066,0.2634654,0.000242448,0.0002481511,0.000924426,0.00143725,0.005559393,0.02312281],"genre_scores_gemma":[0.7300609,0.0003420768,0.2325149,0.0003343321,0.00005746435,0.000816192,0.001076262,0.000535512,0.03426229],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.01108077,"threshold_uncertainty_score":0.0370689,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0614347791593735,"score_gpt":0.3390051774177831,"score_spread":0.2775703982584096,"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."}}