{"id":"W2058546627","doi":"10.1117/12.788244","title":"Managing a big ground-based astronomy project: the Thirty Meter Telescope (TMT) project","year":2008,"lang":"en","type":"article","venue":"Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE","topic":"Technology Assessment and Management","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Ontario Ministry of Research and Innovation; California Institute of Technology; Gordon and Betty Moore Foundation","keywords":"Metre; Telescope; Computer science; Remote sensing; Astronomy; Physics; Geology","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"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":[0.006901873,0.000417171,0.0001153565,0.0007383824,0.002240229,0.003413636,0.0009844983,0.0008849111,0.004118223],"category_scores_gemma":[0.004807151,0.0002384892,0.0002950508,0.0005877637,0.001031121,0.001785039,0.00365134,0.001320616,0.001317169],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002204337,"about_ca_system_score_gemma":0.01065522,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002692009,"about_ca_topic_score_gemma":0.004541283,"domain_scores_codex":[0.9968258,0.001136286,0.0001040403,0.0001698533,0.001383192,0.0003807672],"domain_scores_gemma":[0.9939374,0.0007347441,0.0005210238,0.0005423122,0.001160836,0.003103712],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0005796592,0.001319127,0.03123842,0.0008445925,0.00007952521,0.0021107,0.008543169,0.02564304,0.03748069,0.08289018,0.1102666,0.6990043],"study_design_scores_gemma":[0.0002959172,0.006279917,0.06380069,0.000506867,0.00007437893,0.003990719,0.01606855,0.03174286,0.02298742,0.03851935,0.8155035,0.0002299164],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5819371,0.002197557,0.243998,0.02494968,0.0006854392,0.002945199,0.0009006698,0.002679123,0.1397073],"genre_scores_gemma":[0.7111182,0.00142948,0.2440051,0.001135257,0.0001284546,0.0007207851,0.001139589,0.0004785694,0.03984465],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006901873,"threshold_uncertainty_score":0.03650105,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01621093971114794,"score_gpt":0.2291655923542822,"score_spread":0.2129546526431342,"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."}}