{"id":"W54712862","doi":"","title":"Information and information seeking of novice versus expert lawyers: how experts add value","year":2000,"lang":"en","type":"article","venue":"New Review of Information Behaviour Research","topic":"Legal Education and Practice Innovations","field":"Social Sciences","cited_by":39,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University","funders":"","keywords":"Value (mathematics); Knowledge management; Psychology; Information seeking; Computer science; Information retrieval; Machine learning","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":[0.02168059,0.0002781482,0.001485433,0.003811976,0.001127089,0.00736065,0.001191599,0.003523353,0.004219537],"category_scores_gemma":[0.1396516,0.0004265066,0.0008261182,0.003431736,0.003427167,0.01178003,0.001977592,0.003000668,0.0003041954],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002492293,"about_ca_system_score_gemma":0.002819281,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006775143,"about_ca_topic_score_gemma":0.01283772,"domain_scores_codex":[0.9835296,0.0107162,0.000724397,0.001204815,0.003217651,0.0006073164],"domain_scores_gemma":[0.6358366,0.3423527,0.007431368,0.003483633,0.008680546,0.002215217],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.002327039,0.001276598,0.2218802,0.00553675,0.001020625,0.0005814366,0.02610773,0.000398482,0.00120969,0.02355307,0.009074439,0.707034],"study_design_scores_gemma":[0.0005075819,0.00228216,0.7257133,0.01348798,0.003813194,0.002013656,0.06391586,0.003163586,0.002338061,0.1311524,0.05124564,0.0003665457],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6218365,0.2787769,0.005320305,0.061332,0.0007725535,0.0001256185,0.0002694111,0.00002863372,0.03153797],"genre_scores_gemma":[0.9162866,0.06992752,0.002864133,0.007921053,0.0008109403,0.0000610723,0.0001447093,0.00002457688,0.001959387],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02168059,"threshold_uncertainty_score":0.1146593,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09843256750236813,"score_gpt":0.4607631064108265,"score_spread":0.3623305389084584,"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."}}