{"id":"W2798906024","doi":"10.21307/connections-2017-004","title":"Compositional Equivalence with Actor Attributes: Positional Analysis of the Florentine Families Network","year":2018,"lang":"en","type":"preprint","venue":"Connections","topic":"Social Capital and Networks","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Equivalence (formal languages); Construct (python library); Diagonal; Narrative; Network structure; Computer science; Network analysis; Sociology; Theoretical computer science; Mathematics; Linguistics; Engineering; Pure mathematics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001784047,0.0003323789,0.0003794844,0.00212383,0.001537023,0.002108441,0.0008502327,0.0008756604,0.009289009],"category_scores_gemma":[0.009878898,0.000248606,0.0005611147,0.001914856,0.002396208,0.005358229,0.001856659,0.0008899956,0.0005058551],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001803378,"about_ca_system_score_gemma":0.0005609994,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008090531,"about_ca_topic_score_gemma":0.005073363,"domain_scores_codex":[0.9987481,0.0005991047,0.00004016711,0.0002721987,0.0002337405,0.0001067306],"domain_scores_gemma":[0.9972875,0.001369506,0.000379881,0.0004029807,0.0003883252,0.0001719209],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.00002059855,0.00001334733,0.001631487,0.00001782442,0.000008421362,0.00008833381,0.0009501028,0.009369816,0.0002780532,0.9759329,0.0004820331,0.01120701],"study_design_scores_gemma":[0.000008131819,0.00001590637,0.001517168,0.00003124102,0.00002273622,0.00009687516,0.0007887421,0.1199836,0.0005056371,0.8679463,0.009071806,0.00001176168],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3003002,0.0003617105,0.642557,0.00126309,0.00004247058,0.0001037637,0.0005079436,0.0001480968,0.05471565],"genre_scores_gemma":[0.9622118,0.0001964588,0.03110043,0.0000804725,0.00004543155,0.00007256854,0.0002741554,0.00004410067,0.005974662],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009289009,"threshold_uncertainty_score":0.03107476,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03570022646224989,"score_gpt":0.3027064053693356,"score_spread":0.2670061789070857,"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."}}