{"id":"W1964075510","doi":"10.1111/tran.12044","title":"‘Trusting the numbers’: mineral prospecting, raising finance and the governance of knowledge","year":2013,"lang":"en","type":"article","venue":"Transactions of the Institute of British Geographers","topic":"Mining and Resource Management","field":"Engineering","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Government of Canada","keywords":"Speculation; Raising (metalworking); Corporate governance; Indeterminacy (philosophy); Work (physics); Warrant; Finance; Economics; Prospecting; Capital (architecture); Capital market; Production (economics); Financial market; Business; Market economy; Accounting; Microeconomics; Engineering","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001918089,0.0000924554,0.0001822681,0.00002237193,0.0001616017,0.00002276652,0.0002903422,0.00003540737,0.00001674079],"category_scores_gemma":[0.00001667328,0.00006497462,0.0001531923,0.000342319,0.0008157259,0.0001110545,0.00001779433,0.0001629132,6.008743e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000009375366,"about_ca_system_score_gemma":0.000009415688,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004672244,"about_ca_topic_score_gemma":0.00068943,"domain_scores_codex":[0.9993186,0.00002370987,0.0002811488,0.0001007382,0.0001361276,0.0001396532],"domain_scores_gemma":[0.9995047,0.00005591724,0.0001215538,0.0002515278,0.00005135834,0.00001491159],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.00004089587,0.0001701886,0.004843155,0.001200996,0.0008398877,0.00000215001,0.008274344,0.6214607,0.001673445,0.002366803,0.004251623,0.3548758],"study_design_scores_gemma":[0.01679865,0.0002917589,0.637401,0.01213654,0.002013809,0.0004885384,0.01389215,0.2219876,0.01067237,0.002625864,0.07941342,0.002278313],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9770967,0.002916508,0.003060075,0.0002011139,0.0004882307,0.0004002399,0.00001497267,0.00003746251,0.0157847],"genre_scores_gemma":[0.9982972,0.0004384194,0.0006659027,0.00000795594,0.00002063352,0.0000264165,2.397062e-7,0.00001202077,0.000531279],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6325578,"threshold_uncertainty_score":0.7063066,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005155932685537005,"score_gpt":0.180536891244346,"score_spread":0.175380958558809,"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."}}