{"id":"W2959392664","doi":"10.1101/705392","title":"Network reaction norms: taking into account network position and network plasticity in response to environmental change","year":2019,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Evolutionary Game Theory and Cooperation","field":"Social Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Lethbridge","funders":"National Research Foundation; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs; Leakey Foundation","keywords":"Centrality; Social network (sociolinguistics); Consistency (knowledge bases); Dynamic network analysis; Variation (astronomy); Phenotypic plasticity; Social network analysis; Psychology; Computer science; Mathematics; Ecology; Statistics; Biology; Artificial intelligence; Physics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005158544,0.0005081769,0.0005648176,0.001695161,0.000400749,0.001561326,0.001069508,0.0008470063,0.001513283],"category_scores_gemma":[0.0324791,0.0002869889,0.0008065074,0.001096839,0.001293864,0.0029036,0.001070214,0.0009182365,0.00009944379],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009216127,"about_ca_system_score_gemma":0.0004534426,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00512906,"about_ca_topic_score_gemma":0.004365125,"domain_scores_codex":[0.9979768,0.001086693,0.0001143438,0.0005317724,0.0001878881,0.0001024826],"domain_scores_gemma":[0.9823481,0.01150524,0.003065718,0.001504445,0.0009053883,0.0006712841],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0006083045,0.0003044246,0.3524624,0.0003643569,0.001274468,0.0007746671,0.002365423,0.4481348,0.01662454,0.09271331,0.001356153,0.08301722],"study_design_scores_gemma":[0.0000177176,0.0001322173,0.103803,0.00002394714,0.00009399094,0.0001561338,0.0003383199,0.8262492,0.00136681,0.06683461,0.0009141202,0.00006990058],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7807172,0.0002317567,0.215168,0.0006494941,0.00009070997,0.00006005234,0.0003996118,0.0001911372,0.00249213],"genre_scores_gemma":[0.9862275,0.00005208981,0.01314283,0.00002619095,0.00003512359,0.00005082941,0.0001362189,0.00002916637,0.0003001154],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005158544,"threshold_uncertainty_score":0.02728128,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01578681648383952,"score_gpt":0.238212561574208,"score_spread":0.2224257450903685,"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."}}