{"id":"W2566408286","doi":"10.1002/pra2.2016.14505301021","title":"Publish or perish: Meet the editors a special panel","year":2016,"lang":"en","type":"article","venue":"Proceedings of the Association for Information Science and Technology","topic":"Academic Publishing and Open Access","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Scope (computer science); Publish or perish; Publication; Publishing; Library science; Political science; Process (computing); Engineering ethics; Computer science; Data science; Engineering; Law","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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.02792035,0.002261551,0.002208187,0.002704197,0.008945603,0.01743655,0.003110767,0.02104631,0.03469735],"category_scores_gemma":[0.06214919,0.001364738,0.00193787,0.001340432,0.003235523,0.0101999,0.00820132,0.01755588,0.0215313],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002135169,"about_ca_system_score_gemma":0.008984019,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007831716,"about_ca_topic_score_gemma":0.002727142,"domain_scores_codex":[0.9867193,0.002412987,0.001507639,0.001452802,0.006045979,0.001861287],"domain_scores_gemma":[0.8891542,0.01319963,0.005611243,0.003156359,0.03910437,0.04977416],"domain_codex":null,"domain_gemma":"incentives","domain_candidate":"incentives","domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00003380508,0.00003216829,0.0003333009,0.00008274703,0.000007363523,0.0002431421,0.0001048178,0.00002354937,0.0003112075,0.0002305802,0.9864152,0.01218222],"study_design_scores_gemma":[0.00002511169,0.00006426398,0.0008671795,0.0001946305,0.00001620699,0.0005345073,0.0009829516,0.0001251334,0.0002323498,0.001113054,0.9957912,0.00005355266],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"editorial","genre_gemma":"commentary","genre_scores_codex":[0.00124531,0.004005009,0.001201172,0.4647983,0.518135,0.000239708,0.0001330034,0.0003066218,0.009935929],"genre_scores_gemma":[0.01420855,0.008230742,0.003295532,0.2900661,0.6125904,0.000593064,0.0003268155,0.000552219,0.07013657],"genre_candidate":"commentary","genre_consensus":null,"teacher_disagreement_score":0.9720796,"threshold_uncertainty_score":0.1476587,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04232788349457507,"score_gpt":0.324088271772566,"score_spread":0.2817603882779909,"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."}}