{"id":"W2950799286","doi":"10.82308/47222","title":"Ecology of American martens in northern hardwood forests: resource pulses and resource selection across temporal and spatial scales","year":2013,"lang":"en","type":"article","venue":"eScholarship@McGill (McGill)","topic":"Wildlife Ecology and Conservation","field":"Environmental Science","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"McGill University; New York State Department of Environmental Conservation","keywords":"Marten; Mast (botany); Ecology; Beech; Predation; Geography; Temporal scales; Spatial ecology; Abundance (ecology); Range (aeronautics); Wildlife; Habitat; Biology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002513686,0.00008783406,0.000157626,0.0005300478,0.0003575984,0.0004653462,0.0002029492,0.0002025875,0.000884072],"category_scores_gemma":[0.0004659957,0.0001023859,0.0001350646,0.0004296139,0.0003207212,0.0002451557,0.0002653674,0.0001290872,0.00009559906],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004129558,"about_ca_system_score_gemma":0.0003360795,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05696063,"about_ca_topic_score_gemma":0.1748803,"domain_scores_codex":[0.9999089,0.00001828403,0.000003610224,0.00003021273,0.000018125,0.00002088398],"domain_scores_gemma":[0.9996885,0.00005963221,0.0001053314,0.00001452218,0.00005207477,0.00007998765],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001317979,0.00006436662,0.9750413,0.00002571312,0.00004863297,0.0001147769,0.00111745,0.0002422081,0.008394862,0.00007301558,0.0001057705,0.01464012],"study_design_scores_gemma":[7.967768e-7,0.0000157872,0.9993603,0.000001803052,0.000003537822,0.00002052041,0.0002843938,0.0001151135,0.00003461092,0.00001410283,0.0001479021,0.000001192875],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9995738,0.00009665082,0.00003663015,0.00001804319,6.369577e-7,0.000001263828,0.00003351794,0.000001330495,0.0002382246],"genre_scores_gemma":[0.9994004,0.00009330744,0.0001445714,0.00001404378,0.000001988183,0.00000323212,0.00007283276,9.257355e-7,0.0002687112],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05696063,"threshold_uncertainty_score":0.1132582,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007303156759495522,"score_gpt":0.2063830607860225,"score_spread":0.199079904026527,"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."}}