{"id":"W4398561569","doi":"10.7910/dvn/hhbfjf","title":"Position Bias in Recommender Systems for Digital Libraries (Dataset)","year":2018,"lang":"en","type":"dataset","venue":"Harvard Dataverse","topic":"Recommender Systems and Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Trinity College","funders":"","keywords":"Recommender system; Computer science; Position (finance); Information retrieval; Digital library; World Wide Web; Art; Business","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":[0.001976935,0.00164415,0.0009103484,0.0027761,0.0007730272,0.001962173,0.002066184,0.0020151,0.02289356],"category_scores_gemma":[0.01487063,0.0004443243,0.001113839,0.004368189,0.0004152877,0.001366324,0.001840476,0.00186945,0.04085783],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001601114,"about_ca_system_score_gemma":0.001422485,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01942595,"about_ca_topic_score_gemma":0.0476385,"domain_scores_codex":[0.9978051,0.0005617876,0.0002723829,0.0005069966,0.0006302016,0.0002236168],"domain_scores_gemma":[0.9947016,0.001610081,0.0004706546,0.001593633,0.001263244,0.0003608255],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001452532,0.00009565164,0.006165671,0.0005189246,0.00006458222,0.00003545973,0.00005831425,0.0007882378,0.0001329427,0.000512305,0.9840292,0.007453397],"study_design_scores_gemma":[0.0006282085,0.0001706758,0.04816281,0.0004448263,0.0001193184,0.0004433097,0.0003816774,0.005904954,0.00173246,0.003101978,0.9388141,0.00009584357],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.004929814,0.0003867859,0.0004178886,0.000352312,0.0001042857,0.00004310473,0.9911533,0.000944127,0.001668387],"genre_scores_gemma":[0.005195014,0.0001187766,0.000971524,0.0001152846,0.00002735884,0.0001081568,0.9918188,0.00007501598,0.001570096],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.02289356,"threshold_uncertainty_score":0.07658666,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04842689351382541,"score_gpt":0.2708768531491026,"score_spread":0.2224499596352772,"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."}}