{"id":"W2073136216","doi":"10.5703/1288284314742","title":"Cost/Benefit Analysis of BioMedCentral Membership at a Large Research Institution","year":2012,"lang":"en","type":"article","venue":"","topic":"Health and Medical Research Impacts","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Purdue Pharma (Canada)","funders":"","keywords":"Institution; Computer science; Sociology; Social science","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","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.007689044,0.0007081993,0.0009819472,0.002651678,0.001212681,0.003341944,0.001987864,0.002663252,0.02038777],"category_scores_gemma":[0.03252935,0.0007201738,0.002162776,0.003202713,0.001010513,0.002387943,0.002136996,0.00172886,0.0009885272],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.007609308,"about_ca_system_score_gemma":0.005154498,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01783813,"about_ca_topic_score_gemma":0.01831492,"domain_scores_codex":[0.991246,0.00562154,0.0003241459,0.0004105263,0.0009641771,0.001433546],"domain_scores_gemma":[0.9712061,0.01883554,0.002645744,0.001199908,0.00209807,0.004014597],"domain_codex":null,"domain_gemma":"evaluation","domain_candidate":"evaluation","domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.08416504,0.008202053,0.4785945,0.001568955,0.003308103,0.002860569,0.0008820342,0.1540887,0.005527054,0.02903183,0.0176888,0.2140823],"study_design_scores_gemma":[0.00758636,0.02543405,0.6235569,0.0003844105,0.009248183,0.003187968,0.008023819,0.2891731,0.00551039,0.01276821,0.01474177,0.0003846819],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9688987,0.001866578,0.003676516,0.003996318,0.00009576434,0.0009025965,0.003527382,0.0001370072,0.01689921],"genre_scores_gemma":[0.9958435,0.0002259283,0.001301921,0.0002396114,0.00003792504,0.00009906109,0.0005348327,0.00001442358,0.001702933],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.996658,"threshold_uncertainty_score":0.06820387,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.5369609201368198,"score_gpt":0.5646568686158508,"score_spread":0.02769594847903101,"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."}}