{"id":"W2091968160","doi":"10.1002/ece3.899","title":"A comparison of abundance estimates from extended batch‐marking and Jolly–Seber‐type experiments","year":2013,"lang":"en","type":"article","venue":"Ecology and Evolution","topic":"Census and Population Estimation","field":"Mathematics","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University; University of Victoria","funders":"Engineering and Physical Sciences Research Council","keywords":"Estimator; Statistics; Maximum likelihood; Sample size determination; Sample (material); Mean squared error; Abundance (ecology); Mathematics; Computer science; Chromatography; Biology; Chemistry","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":[0.01625163,0.0006626801,0.001258293,0.0009903861,0.000523474,0.0007784802,0.001824437,0.001040016,0.001673656],"category_scores_gemma":[0.03510841,0.0005009765,0.001127434,0.0005528908,0.001142122,0.001729222,0.001207543,0.001259477,0.0003967529],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001033368,"about_ca_system_score_gemma":0.0004722911,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002042489,"about_ca_topic_score_gemma":0.003589816,"domain_scores_codex":[0.9940083,0.002780714,0.0003308832,0.001795044,0.0009328287,0.0001523622],"domain_scores_gemma":[0.9504711,0.03239715,0.004010222,0.009154478,0.003281072,0.0006859222],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.01041025,0.001184246,0.2542535,0.001435627,0.002252693,0.0004919164,0.004948495,0.04209978,0.4668216,0.01678068,0.002219772,0.1971014],"study_design_scores_gemma":[0.0004146409,0.005625132,0.7137167,0.0001864322,0.00131822,0.00106132,0.0006850872,0.1588726,0.09439897,0.01584827,0.007321563,0.0005510976],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.79087,0.0008605733,0.2036305,0.0002092542,0.0001032073,0.0002197663,0.0008103161,0.0004085308,0.002887848],"genre_scores_gemma":[0.8747424,0.0003267353,0.1192244,0.0003492005,0.0000496738,0.0006131931,0.001901877,0.0003238438,0.002468772],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01625163,"threshold_uncertainty_score":0.08594793,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05207130767094047,"score_gpt":0.3582084870280379,"score_spread":0.3061371793570974,"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."}}