{"id":"W65200891","doi":"10.1007/0-306-47015-2_39","title":"Large Imagery Data Structuring Using Hierarchical Data Format for Parallel Computing and Visualization","year":2005,"lang":"en","type":"book-chapter","venue":"Kluwer Academic Publishers eBooks","topic":"Geochemistry and Geologic Mapping","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada; Sichuan University of Science and Engineering","keywords":"Structuring; Computer science; Visualization; Context (archaeology); Data science; Earth observation satellite; Satellite; Data mining; Earth science; Geography; Engineering; Geology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","scholarly_communication","open_science"],"consensus_categories":["open_science"],"category_scores_codex":[0.001794603,0.0005745931,0.0005999517,0.0002420951,0.0004852837,0.001112222,0.005817772,0.00102297,0.00002605515],"category_scores_gemma":[0.0003902935,0.0005890955,0.00007756332,0.00004714137,0.0001900446,0.004002845,0.01013233,0.001711561,0.000002750402],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008468318,"about_ca_system_score_gemma":0.000293235,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000679388,"about_ca_topic_score_gemma":0.000003719258,"domain_scores_codex":[0.9958762,0.00004619487,0.0008965062,0.001807859,0.0005189877,0.0008542364],"domain_scores_gemma":[0.9959431,0.0002948334,0.0006441035,0.002682309,0.0001702024,0.000265505],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001015838,0.00003869773,0.00017683,0.001935657,0.0006759028,0.00007222524,0.003874061,0.0006297737,0.0005065242,0.544113,0.270845,0.1770307],"study_design_scores_gemma":[0.0005060929,0.0000101069,0.000007427462,0.0002128011,0.00005527005,0.0001204974,0.00002519256,0.452781,0.00001696833,0.03494354,0.5107716,0.0005495007],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00009270301,0.0008184658,0.8334286,0.00108185,0.0006939403,0.0008284511,0.0004279973,0.0004078819,0.1622201],"genre_scores_gemma":[0.04750262,0.0002429304,0.4998735,0.008011298,0.01072056,0.00004496362,0.02025868,0.0003692233,0.4129762],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.5091695,"threshold_uncertainty_score":0.9999247,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07886378001765157,"score_gpt":0.3169605240906945,"score_spread":0.2380967440730429,"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."}}