{"id":"W4320039937","doi":"10.1007/s40823-023-00084-z","title":"Contextualising Landscape Ecology in Wildlife and Forest Conservation in India: a Review","year":2023,"lang":"en","type":"review","venue":"Current Landscape Ecology Reports","topic":"Wildlife Ecology and Conservation","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Wildlife; Geography; Landscape ecology; Ecology; Biodiversity; Environmental resource management; Biodiversity hotspot; Habitat; Wildlife conservation; Applied ecology; Thematic map; Wildlife management; Spatial ecology; Environmental science; Biology; Cartography","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.002232764,0.0005548454,0.002295816,0.0004471385,0.0001252089,0.00002683982,0.0002431804,0.0008224,0.0007029736],"category_scores_gemma":[0.00117612,0.0005100125,0.0001854121,0.001093954,0.0002481926,0.0002454429,0.0004230075,0.0009792099,0.0002975272],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002672574,"about_ca_system_score_gemma":0.0003032955,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004989059,"about_ca_topic_score_gemma":0.007758222,"domain_scores_codex":[0.9951803,0.0007130547,0.002047477,0.001146473,0.0002104621,0.0007022517],"domain_scores_gemma":[0.9971216,0.0008866265,0.00134003,0.0004906908,0.00002207807,0.0001390021],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000005700076,0.0001121108,0.919385,0.005586934,0.00003148733,0.0007391343,0.00004998053,0.000005380017,1.092287e-8,0.00002592657,0.03493364,0.03912472],"study_design_scores_gemma":[0.0003293223,0.00005503734,0.6330127,0.007870316,0.0001818785,0.0005980529,0.00001320044,0.0000621753,4.191468e-9,0.0002102575,0.357283,0.0003840759],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.03199825,0.962249,0.000001491661,0.0006249797,0.001706463,0.00249119,0.00001415876,0.00008814908,0.0008262941],"genre_scores_gemma":[0.001544055,0.9953771,0.00001279812,0.001088953,0.0001106301,0.00101726,0.0006318309,0.00005405807,0.0001633544],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.3223493,"threshold_uncertainty_score":0.9997352,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03972619092159922,"score_gpt":0.315379034120612,"score_spread":0.2756528431990128,"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."}}