{"id":"W2151383676","doi":"10.1111/2041-210x.12383","title":"Generalized affiliation indices extract affiliations from social network data","year":2015,"lang":"en","type":"article","venue":"Methods in Ecology and Evolution","topic":"Plant and animal studies","field":"Agricultural and Biological Sciences","cited_by":84,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"Natural Sciences and Engineering Research Council of Canada; Universität Bielefeld; Fisheries and Oceans Canada; National Institute for Mathematical and Biological Synthesis; World Wildlife Fund","keywords":"Deviance (statistics); Generalized linear model; Statistics; Mathematics; Multivariate statistics; Negative binomial distribution; Linear regression; Poisson distribution; Econometrics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001072023,0.00007405667,0.0001534153,0.00001047392,0.0002522031,0.00001728104,0.0001329848,0.0001392849,0.00003395977],"category_scores_gemma":[0.0002350474,0.000034958,0.00001533191,0.0001782648,0.0000546917,0.0001607679,0.0001334153,0.00009606908,0.000007486536],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003684276,"about_ca_system_score_gemma":0.000008204261,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005797099,"about_ca_topic_score_gemma":0.02257414,"domain_scores_codex":[0.9989243,0.0004558711,0.0001536896,0.0002274705,0.00005886814,0.0001798048],"domain_scores_gemma":[0.999431,0.0004079716,0.00008180318,0.00002122287,0.00002318877,0.00003488209],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00008085406,0.00005905039,0.9486499,0.000001254449,0.00001952791,0.000001614726,0.0002271748,0.00003474004,0.008278366,0.001016528,0.004890626,0.0367403],"study_design_scores_gemma":[0.000168598,0.00004776383,0.9769557,0.000002505717,0.00001455423,9.706342e-7,0.0002872397,0.002301271,0.00001507608,0.01490247,0.005223955,0.00007986433],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9969851,0.0009586935,0.0003636332,0.0009773893,0.0002109273,0.00008369816,0.00008282645,0.00003145168,0.000306305],"genre_scores_gemma":[0.9736851,0.0001107385,0.02507339,0.00009504281,0.0006661318,0.00001144775,0.0003113162,4.609648e-7,0.00004641373],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03666043,"threshold_uncertainty_score":0.9952613,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.198317614648897,"score_gpt":0.3628179260597155,"score_spread":0.1645003114108185,"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."}}