{"id":"W3208496800","doi":"10.1017/nws.2021.18","title":"Measuring reciprocity: Double sampling, concordance, and network construction","year":2021,"lang":"en","type":"article","venue":"Network Science","topic":"Social Capital and Networks","field":"Social Sciences","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Social Sciences and Humanities Research Council of Canada; Max-Planck-Institut für Evolutionäre Anthropologie; National Science Foundation","keywords":"Reciprocity (cultural anthropology); Concordance; Interpersonal ties; Social psychology; Exponential random graph models; Psychology; Computer science; Graph; Theoretical computer science; Random graph","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.002298649,0.000131159,0.0002196826,0.00003030295,0.003229219,0.0004229267,0.0003084616,0.0001213717,0.00009183208],"category_scores_gemma":[0.0001984314,0.0001403444,0.0000527274,0.002366626,0.002387424,0.0005403465,0.0002027445,0.0002522251,0.00001625011],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002010168,"about_ca_system_score_gemma":0.0007424738,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003617076,"about_ca_topic_score_gemma":0.002494818,"domain_scores_codex":[0.9974901,0.0001202554,0.0002245636,0.0005410067,0.0007162509,0.0009077919],"domain_scores_gemma":[0.99883,0.0001857703,0.0001234715,0.0001963266,0.0003635331,0.0003008801],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00008072004,0.00004739561,0.0800826,0.00001615381,0.00002942664,0.00002468845,0.008999517,0.003091614,0.0002697873,0.7075653,0.008988522,0.1908042],"study_design_scores_gemma":[0.002106997,0.0001432358,0.06526312,0.0005929072,0.0001019204,0.00008372343,0.01861716,0.001564948,0.0005239389,0.1956707,0.7135565,0.001774831],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6909063,0.006282455,0.002402338,0.001729359,0.007314143,0.0004114869,0.000001626434,0.0003233738,0.2906289],"genre_scores_gemma":[0.9804795,0.001712303,0.01071795,0.0008561155,0.005241517,0.00001947365,0.000002197396,0.00001352077,0.0009574613],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.704568,"threshold_uncertainty_score":0.9980685,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06435775719973422,"score_gpt":0.3085600578360818,"score_spread":0.2442023006363475,"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."}}