{"id":"W3086645187","doi":"10.1109/iri49571.2020.00045","title":"Using a Deep Learning Model, Content Features, and Author Metadata to Recommend Research Papers","year":2020,"lang":"en","type":"article","venue":"","topic":"Recommender Systems and Techniques","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Metadata; Popularity; Quality (philosophy); Jungle; World Wide Web; Publishing; Recommender system; Information retrieval; Data science; Collaborative filtering","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001056076,0.0001314423,0.0002165121,0.0001183578,0.0002721526,0.0006596243,0.0006588111,0.00006527706,0.00001021311],"category_scores_gemma":[0.0001350777,0.0001054631,0.00003736794,0.0003983794,0.00002087268,0.0005889141,0.001035536,0.0003889444,0.000004395381],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004473567,"about_ca_system_score_gemma":0.00003358788,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004021306,"about_ca_topic_score_gemma":0.00005828642,"domain_scores_codex":[0.9982762,0.00026356,0.0002138772,0.0005463783,0.0003372781,0.0003627352],"domain_scores_gemma":[0.9990731,0.0001075807,0.00003963212,0.0003496946,0.00009921358,0.0003308093],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00007048334,0.00009994851,0.0009565438,0.0001668624,0.0002027556,0.00008791991,0.01537937,0.001845551,0.07008121,0.3081523,0.07002009,0.5329369],"study_design_scores_gemma":[0.0002519549,0.00033024,0.0001275979,0.00004854357,0.00000711711,0.00005063971,0.000881773,0.9014629,0.004012502,0.0009395508,0.09154634,0.0003408842],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.001556392,0.0002741952,0.9645752,0.02524677,0.00005937723,0.0003553625,0.000001258881,0.000289648,0.007641773],"genre_scores_gemma":[0.5348705,0.00003084874,0.4610041,0.002340962,0.00004811723,0.00002421597,0.000001547439,0.00001541634,0.001664292],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8996173,"threshold_uncertainty_score":0.6360772,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4279885983222725,"score_gpt":0.4016992480998558,"score_spread":0.02628935022241674,"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."}}