{"id":"W7079553245","doi":"10.5281/zenodo.17018324","title":"What price is free?","year":2025,"lang":"en","type":"report","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Geochemistry and Geologic Mapping","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Research England","keywords":"Entitlement (fair division); Government (linguistics); Unintended consequences; Quarter (Canadian coin); Incentive; Public policy","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002569297,0.0002138696,0.0004745746,0.0006944881,0.003336303,0.00697866,0.000855599,0.004527787,0.08544334],"category_scores_gemma":[0.02384866,0.0002082138,0.0004219816,0.0009238402,0.003671304,0.009411513,0.001617809,0.006356721,0.01358494],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005280212,"about_ca_system_score_gemma":0.004579415,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01659594,"about_ca_topic_score_gemma":0.01832305,"domain_scores_codex":[0.9972989,0.0007876596,0.000130137,0.0003011309,0.0008809053,0.0006012204],"domain_scores_gemma":[0.9942914,0.001475911,0.0004795067,0.0002011848,0.001158552,0.0023935],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00005899679,0.00009906333,0.004126718,0.0001087257,0.00001244124,0.0002498466,0.001422283,0.0000355892,0.00006239599,0.07025757,0.8201033,0.1034631],"study_design_scores_gemma":[0.00002752761,0.00005265505,0.005157611,0.0004850344,0.00001000519,0.0005329965,0.005075406,0.0000892364,0.0001001104,0.03641694,0.9520136,0.00003874133],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"other","genre_scores_codex":[0.007354464,0.01113358,0.0005561151,0.8438291,0.01083192,0.00002091998,0.0003791963,0.00004619851,0.1258485],"genre_scores_gemma":[0.2895038,0.02722179,0.0009848361,0.4242316,0.009986684,0.00008136592,0.0007987968,0.0002602971,0.2469309],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.08544334,"threshold_uncertainty_score":0.2858365,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0467392349611155,"score_gpt":0.262692731693469,"score_spread":0.2159534967323535,"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."}}