{"id":"W6929742458","doi":"10.5061/dryad.qbzkh18p5","title":"Social interactions generate complex selection patterns in virtual worlds","year":2024,"lang":"en","type":"dataset","venue":"DRYAD","topic":"Reliability and Agreement in Measurement","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Montréal","funders":"Mitacs; European Commission","keywords":"Selection (genetic algorithm); Natural selection; Natural (archaeology); Social relation; Variation (astronomy); Inclusive fitness; Mechanism (biology)","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":[0.0007073669,0.0002832202,0.0004221651,0.001075965,0.0005265918,0.001269634,0.0003812774,0.0003242534,0.002402909],"category_scores_gemma":[0.006801003,0.0002556352,0.0003265503,0.0004665327,0.0008283092,0.0006960469,0.001313251,0.0003321578,0.0002396969],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002852875,"about_ca_system_score_gemma":0.0001437592,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001531865,"about_ca_topic_score_gemma":0.002385889,"domain_scores_codex":[0.9991572,0.0004485382,0.00002462233,0.0001318375,0.0001388373,0.00009891367],"domain_scores_gemma":[0.9966446,0.001998767,0.000531137,0.0003026723,0.0002074879,0.00031537],"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":[0.001178516,0.0004968025,0.656567,0.0003761553,0.000945074,0.001495266,0.007766572,0.1025986,0.05557721,0.03540897,0.004705862,0.1328841],"study_design_scores_gemma":[0.00004080826,0.000255464,0.730036,0.0000398621,0.0001156885,0.0007781358,0.002531358,0.2330672,0.00187612,0.02829299,0.002870773,0.00009563014],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"dataset","genre_scores_codex":[0.9916152,0.0000732504,0.006278847,0.00005044861,0.000005251128,0.00001268542,0.00007494216,0.00003785452,0.001851584],"genre_scores_gemma":[0.9985958,0.00001577611,0.001098679,0.00001054843,0.000002954258,0.00001103883,0.00006494219,0.000009314607,0.000190966],"genre_candidate":"dataset","genre_consensus":null,"teacher_disagreement_score":0.002402909,"threshold_uncertainty_score":0.008038521,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2379732638707709,"score_gpt":0.4434277590926073,"score_spread":0.2054544952218364,"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."}}