{"id":"W2954863312","doi":"10.1101/694166","title":"Reciprocity and behavioral heterogeneity govern the stability of social networks","year":2019,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Animal Behavior and Reproduction","field":"Agricultural and Biological Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Reciprocity (cultural anthropology); Social connectedness; Social network (sociolinguistics); Stability (learning theory); General partnership; Social psychology; Psychology; Economics; Computer science; Social media; Machine learning","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":[0.001445623,0.0001769588,0.000360945,0.0008090078,0.0005466088,0.00126443,0.0004652182,0.0005644883,0.001977598],"category_scores_gemma":[0.01340257,0.0002543127,0.0003984774,0.0004645906,0.001205284,0.001441225,0.000721017,0.0003659356,0.0002347568],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000730863,"about_ca_system_score_gemma":0.0003316771,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003295871,"about_ca_topic_score_gemma":0.003131948,"domain_scores_codex":[0.9993223,0.0003186004,0.00004018986,0.0001445031,0.00007983826,0.00009468233],"domain_scores_gemma":[0.9926707,0.00347573,0.002317549,0.0006570556,0.0004310441,0.0004478404],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003627307,0.0001736576,0.6579626,0.0002439971,0.0006348995,0.000719725,0.001751441,0.2074939,0.029614,0.0661751,0.001775607,0.03309232],"study_design_scores_gemma":[0.000053228,0.0002037443,0.3316658,0.00004471671,0.0001734057,0.0006977455,0.0009411873,0.5884318,0.002728925,0.07328273,0.001684347,0.00009231984],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9865789,0.0001329613,0.01085568,0.0001953702,0.000005516507,0.00001503643,0.0001008266,0.00003142367,0.002084304],"genre_scores_gemma":[0.9994054,0.00002032424,0.0004459806,0.000005406542,0.00000253115,0.000004568414,0.00001483999,0.000002399662,0.0000986124],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003295871,"threshold_uncertainty_score":0.007645249,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03353670174838684,"score_gpt":0.2378457696280692,"score_spread":0.2043090678796823,"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."}}