{"id":"W2981361409","doi":"10.1071/wr18122","title":"Estimating kangaroo density by aerial survey: a comparison of thermal cameras with human observers","year":2019,"lang":"en","type":"article","venue":"Wildlife Research","topic":"Wildlife Ecology and Conservation","field":"Environmental Science","cited_by":61,"is_retracted":false,"has_abstract":true,"ca_institutions":"Lethbridge College","funders":"","keywords":"Aerial survey; Wildlife; Transect; Wildlife management; Geography; Population; Ecology; Distance sampling; Habitat; Animal ecology; Population density; Camera trap; Wildlife conservation; Human–wildlife conflict; Survey methodology; Photogrammetry; Remote sensing; Biology; Statistics; Demography; Mathematics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002842131,0.0003951446,0.0002868459,0.001401052,0.0002053389,0.0005447426,0.0004054174,0.0003545856,0.001066389],"category_scores_gemma":[0.01058875,0.0002437204,0.0003729716,0.0005930614,0.0002998452,0.0007686495,0.0005667474,0.0001824464,0.0004269638],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003306145,"about_ca_system_score_gemma":0.0001471027,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004526384,"about_ca_topic_score_gemma":0.008834611,"domain_scores_codex":[0.9973114,0.001467034,0.0002272652,0.0004347531,0.0004747433,0.00008482857],"domain_scores_gemma":[0.9917526,0.004080972,0.001824436,0.0003970846,0.001728088,0.0002168435],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001157636,0.0001553951,0.9286449,0.0003721527,0.0003328184,0.0001197863,0.002119623,0.002330076,0.008337136,0.00008651876,0.0002726176,0.05607134],"study_design_scores_gemma":[0.00002639682,0.00137171,0.9788681,0.00009832887,0.0001971816,0.0005369719,0.002621316,0.01185956,0.003532474,0.00008874831,0.0007551956,0.00004401597],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9915474,0.0002982861,0.005606507,0.00002039666,0.00001425252,0.00009874978,0.0003112928,0.00003807626,0.002065009],"genre_scores_gemma":[0.9933608,0.0001445109,0.005871636,0.00001706164,0.000009188464,0.00005122577,0.0002343079,0.000005868873,0.0003053353],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004526384,"threshold_uncertainty_score":0.0150308,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06558777232214827,"score_gpt":0.3466673594029797,"score_spread":0.2810795870808315,"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."}}