{"id":"W6994499722","doi":"","title":"eAccess to Justice","year":2016,"lang":"en","type":"other","venue":"OAPEN (The OAPEN Foundation)","topic":"Media and Digital Communication","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"European Commission; Social Sciences and Humanities Research Council of Canada; McGill University","keywords":"Economic Justice; Digitization; Leverage (statistics); Criminal justice; Information and Communications Technology","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"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":[0.004413682,0.000430994,0.0004012827,0.001771942,0.00874531,0.0203198,0.001158279,0.007610434,0.05892379],"category_scores_gemma":[0.01839556,0.0002202444,0.0004424112,0.002012928,0.0160207,0.01732674,0.01145441,0.006233681,0.008052567],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006803676,"about_ca_system_score_gemma":0.01355523,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008917391,"about_ca_topic_score_gemma":0.01294893,"domain_scores_codex":[0.9928781,0.002571856,0.0002273329,0.000801971,0.002215503,0.001305144],"domain_scores_gemma":[0.9950164,0.00196013,0.0003292614,0.0009480699,0.0006999915,0.001046213],"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":[0.00001065855,0.00002028989,0.000267045,0.00008662492,0.000003423796,0.00006915411,0.003256071,0.00005954661,0.00006992364,0.7470465,0.188284,0.06082674],"study_design_scores_gemma":[0.000002014004,0.000005050078,0.0002208318,0.0002436252,0.000001689396,0.0000608948,0.002326434,0.00003136587,0.00008671667,0.06478655,0.9322296,0.000005145842],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.002920235,0.02023749,0.001528308,0.1823969,0.004876818,0.00003121228,0.0001142095,0.0001076645,0.7877871],"genre_scores_gemma":[0.1903968,0.02755477,0.002056605,0.07092677,0.004333711,0.0001501756,0.0002367323,0.0003149772,0.7040294],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.05892379,"threshold_uncertainty_score":0.1971197,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02731508068220916,"score_gpt":0.3115890730818623,"score_spread":0.2842739923996531,"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."}}