{"id":"W2560241432","doi":"10.1109/bigdata.2016.7840982","title":"Understanding computational web archives research methods using research objects","year":2016,"lang":"en","type":"article","venue":"","topic":"Scientific Computing and Data Management","field":"Decision Sciences","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo; University of Toronto","funders":"","keywords":"Computer science; World Wide Web; Data science; Information retrieval","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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.09803583,0.001171111,0.001408928,0.0140497,0.005836482,0.03045463,0.004962069,0.003987156,0.003489725],"category_scores_gemma":[0.1222188,0.001561334,0.002607211,0.01428406,0.02616215,0.03292723,0.009418651,0.004022612,0.0007087478],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.007546823,"about_ca_system_score_gemma":0.01791161,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007153117,"about_ca_topic_score_gemma":0.004676115,"domain_scores_codex":[0.9157306,0.06582687,0.005206536,0.004037147,0.008060081,0.001138722],"domain_scores_gemma":[0.7596592,0.1843048,0.01133961,0.03717346,0.006328512,0.001194396],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.000009350314,0.00002646231,0.001133943,0.00016679,0.00002126396,0.00008333342,0.00535214,0.002584521,0.000140038,0.9758744,0.000292799,0.01431504],"study_design_scores_gemma":[0.00002987934,0.00002473454,0.0006027475,0.0004372276,0.0000293596,0.0001235867,0.004571125,0.01798471,0.0007500603,0.9475952,0.02781461,0.00003678097],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01119718,0.0007715551,0.972006,0.003936152,0.0000594737,0.0004923779,0.0001548876,0.0002694324,0.01111288],"genre_scores_gemma":[0.1047689,0.0009023161,0.8909611,0.0002410399,0.00005864194,0.001277801,0.0002184224,0.0001352934,0.001436568],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9019642,"threshold_uncertainty_score":0.5184692,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.9498805506634593,"score_gpt":0.6930932414658175,"score_spread":0.2567873091976418,"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."}}