{"id":"W2602894607","doi":"","title":"Multi-dimensional Ratings for Research Paper Recommender Systems: A Qualitative Study","year":2015,"lang":"en","type":"preprint","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Recommender Systems and Techniques","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Recommender system; Computer science; Qualitative research; Data science; Information retrieval; Artificial intelligence; Sociology","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":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch","metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.05665491,0.0005055544,0.000775087,0.000494135,0.0007476266,0.001546286,0.003512458,0.0004117737,0.00001683897],"category_scores_gemma":[0.002831439,0.000482112,0.0002546244,0.0006310346,0.0001819313,0.0004845927,0.00465677,0.001228937,0.00002999941],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004326127,"about_ca_system_score_gemma":0.0008300198,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005072227,"about_ca_topic_score_gemma":0.001388908,"domain_scores_codex":[0.965544,0.02966928,0.00115756,0.00169912,0.00120516,0.0007248019],"domain_scores_gemma":[0.9790764,0.005708374,0.0007792383,0.003721824,0.01037033,0.0003438673],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00004274663,0.005600353,0.0003291108,0.0008236644,0.0006125001,0.00001543863,0.5779077,0.0001125189,0.001028148,0.2415056,0.1514384,0.0205839],"study_design_scores_gemma":[0.008915436,0.00004427665,0.0007253313,0.01162669,0.0001609937,0.00006885645,0.06971794,0.6154594,0.009568408,0.09295839,0.1861263,0.004627998],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01112079,0.001626648,0.9565688,0.0152428,0.0009896602,0.004928116,0.0001043595,0.0008117792,0.008606981],"genre_scores_gemma":[0.5832188,0.00005431319,0.4047307,0.0001384614,0.00006667463,0.002536954,0.000215773,0.00008569402,0.008952678],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.6153469,"threshold_uncertainty_score":0.9997631,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1422951111323976,"score_gpt":0.3913246803867984,"score_spread":0.2490295692544007,"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."}}