{"id":"W6948372259","doi":"10.5061/dryad.kv2kh","title":"Data from: Direction matching for sparse movement data sets: determining interaction rules in social groups","year":2016,"lang":"en","type":"dataset","venue":"Data Archiving and Networked Services (DANS)","topic":"","field":"","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Lethbridge","funders":"","keywords":"Movement (music); Matching (statistics); Set (abstract data type); Data set; Test (biology); Baboon; Group (periodic table); Motion (physics)","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":[0.005067494,0.0006471497,0.0007745753,0.002887992,0.0006972596,0.001228326,0.001389306,0.001441049,0.004667032],"category_scores_gemma":[0.0262968,0.0004429884,0.001231645,0.002964969,0.0006542488,0.001425802,0.001786726,0.001003723,0.003535202],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004351014,"about_ca_system_score_gemma":0.0009315725,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004949585,"about_ca_topic_score_gemma":0.008422196,"domain_scores_codex":[0.9976336,0.0008175387,0.0003349593,0.0005658056,0.000514405,0.0001336744],"domain_scores_gemma":[0.9912127,0.003445827,0.001040221,0.002970984,0.001059941,0.0002703821],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.002699502,0.001087683,0.3792644,0.0025315,0.001150255,0.001400822,0.003328457,0.05102369,0.03254546,0.01211748,0.09937453,0.4134763],"study_design_scores_gemma":[0.0007032497,0.0008641985,0.4498282,0.0004833646,0.0002910557,0.001342549,0.002036776,0.3607063,0.0215236,0.03026348,0.1316128,0.0003444388],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"dataset","genre_scores_codex":[0.4387848,0.0007373439,0.3257642,0.002010103,0.0005662098,0.002094818,0.2045639,0.01544182,0.01003683],"genre_scores_gemma":[0.4859552,0.000228481,0.3394049,0.0002343868,0.0001026939,0.002125562,0.1690536,0.0007447901,0.002150506],"genre_candidate":"dataset","genre_consensus":null,"teacher_disagreement_score":0.005067494,"threshold_uncertainty_score":0.0267998,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08296742218008381,"score_gpt":0.3424405341801058,"score_spread":0.259473112000022,"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."}}