{"id":"W2481036003","doi":"10.1057/9780230283145_12","title":"Collecting for the Science Museum: Constructing the Collections, the Culture and the Institution","year":2010,"lang":"en","type":"book-chapter","venue":"Palgrave Macmillan UK eBooks","topic":"Museums and Cultural Heritage","field":"Arts and Humanities","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Institution; Quarter (Canadian coin); Cover (algebra); State (computer science); History; History of science; Art history; Computer science; Archaeology; Engineering; Sociology; Social science; Epistemology; Philosophy","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":["sts"],"consensus_categories":[],"category_scores_codex":[0.001252549,0.0006636233,0.0003193686,0.002375379,0.00801533,0.01157985,0.001191636,0.001445781,0.01452569],"category_scores_gemma":[0.001691849,0.0006725742,0.0002623729,0.004484536,0.01137906,0.007734092,0.003804285,0.003635714,0.004630113],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01146197,"about_ca_system_score_gemma":0.01786617,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.06230054,"about_ca_topic_score_gemma":0.1655222,"domain_scores_codex":[0.9991721,0.0003082248,0.0000347696,0.0000991246,0.0002857132,0.0001000973],"domain_scores_gemma":[0.9996086,0.00009972527,0.00002807659,0.00006964137,0.0001065958,0.00008729388],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"qualitative","study_design_scores_codex":[0.000008144772,0.00001784679,0.0003662834,0.000148431,0.000004274897,0.00009615378,0.01682783,0.0001352263,0.0001679186,0.5612363,0.3453916,0.07559995],"study_design_scores_gemma":[0.00000116713,0.000002091548,0.0003819534,0.0001566814,0.000001650208,0.00005046749,0.003637602,0.00001930165,0.00006007818,0.01414378,0.9815398,0.000005451368],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.002134425,0.0194557,0.002222182,0.008917625,0.001180781,0.00006767987,0.0002117996,0.0001383297,0.9656715],"genre_scores_gemma":[0.05745703,0.02870043,0.01043241,0.003435316,0.000779134,0.000243803,0.0004505119,0.0005454389,0.8979559],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9919847,"threshold_uncertainty_score":0.1238758,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03266684877926303,"score_gpt":0.2317488476639954,"score_spread":0.1990819988847324,"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."}}