{"id":"W4402842634","doi":"10.3998/ticker.6410","title":"But I Need It!  Exploring a Magic Quadrant for Collections Needs, Wants and Contributions  ","year":2024,"lang":"en","type":"article","venue":"Ticker The Academic Business Librarianship Review","topic":"Intellectual Property Law","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.01592721,0.0007713212,0.0005895504,0.007636209,0.0130659,0.036593,0.002182606,0.003968408,0.01710019],"category_scores_gemma":[0.02233851,0.0007540459,0.0007734903,0.008844892,0.03185619,0.04582491,0.01377245,0.007790371,0.002158281],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01441757,"about_ca_system_score_gemma":0.01405576,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02181709,"about_ca_topic_score_gemma":0.04629138,"domain_scores_codex":[0.9871164,0.008901832,0.0003400983,0.000507073,0.002143992,0.0009905559],"domain_scores_gemma":[0.9843733,0.009600661,0.0008993254,0.0007022115,0.002842984,0.001581457],"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":[0.00002784606,0.00003212467,0.001607557,0.0002026243,0.000009606551,0.0003919471,0.07200924,0.000227224,0.0002857981,0.7837332,0.09911698,0.04235586],"study_design_scores_gemma":[0.00001686942,0.00003643681,0.001410978,0.0004982775,0.000008297987,0.0002762745,0.2399175,0.0006863166,0.0001877581,0.2720163,0.4848807,0.0000642692],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.05344874,0.008778553,0.03785899,0.4741502,0.001620846,0.0002398742,0.0004422864,0.0004739677,0.4229867],"genre_scores_gemma":[0.836677,0.01028462,0.06098674,0.03569988,0.0007628211,0.0004921335,0.0003875557,0.0005380565,0.05417126],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.963407,"threshold_uncertainty_score":0.1046073,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1803060695207093,"score_gpt":0.3548041342689646,"score_spread":0.1744980647482553,"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."}}