{"id":"W4251842006","doi":"10.1007/978-1-4939-7131-2_100021","title":"Almost Network Data","year":2018,"lang":"en","type":"book-chapter","venue":"","topic":"Opportunistic and Delay-Tolerant Networks","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Computer science","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":[0.0005957286,0.0006318956,0.000469339,0.000926214,0.0007980851,0.002759877,0.00111232,0.0007969516,0.03730193],"category_scores_gemma":[0.004190702,0.0003054733,0.0002557442,0.001703023,0.001247642,0.006680942,0.002083923,0.001761645,0.01293701],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009227041,"about_ca_system_score_gemma":0.0006401431,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007611605,"about_ca_topic_score_gemma":0.0006927727,"domain_scores_codex":[0.9993809,0.00008773684,0.00002800208,0.0001202777,0.0003383907,0.00004464902],"domain_scores_gemma":[0.998871,0.0002927038,0.00004403836,0.0005397811,0.0001958156,0.00005665757],"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":[0.00005559687,0.0000165902,0.0001279717,0.0001620816,0.00001135701,0.00003856279,0.0001073133,0.002695421,0.001074342,0.7134574,0.1049177,0.1773357],"study_design_scores_gemma":[0.000008920844,0.00001361299,0.0001105141,0.00008036644,0.00000768456,0.0001330515,0.0000584117,0.006995191,0.001286768,0.4241289,0.567165,0.00001158389],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.007253227,0.009284294,0.3308713,0.01102243,0.005961963,0.0001512354,0.003959165,0.002767904,0.6287283],"genre_scores_gemma":[0.2429402,0.01524019,0.1133733,0.005218446,0.004652112,0.000521412,0.007858111,0.001941602,0.6082546],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.03730193,"threshold_uncertainty_score":0.1247874,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0844839093837426,"score_gpt":0.2605157526739513,"score_spread":0.1760318432902087,"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."}}