{"id":"W2003833411","doi":"10.1109/whispers.2011.6080877","title":"MR-i — overview and first results of the ABB high speed hyperspectral imaging spectroradiometer","year":2011,"lang":"en","type":"article","venue":"","topic":"Spectroscopy and Chemometric Analyses","field":"Chemistry","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"ABB (Canada)","funders":"","keywords":"Hyperspectral imaging; Spectroradiometer; Modular design; Product line; Full spectral imaging; Spectral imaging; Image resolution; Computer science; Chemical imaging; Remote sensing; Imaging spectroscopy; Spectral resolution; Spectral signature; Moderate-resolution imaging spectroradiometer; Artificial intelligence; Computer vision; Optics; Physics; Engineering; Geology; Spectral line; Reflectivity; Satellite","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002145342,0.001016807,0.0007394578,0.001240342,0.0003436235,0.001899716,0.001083342,0.0008135089,0.01332248],"category_scores_gemma":[0.001491374,0.0005205361,0.0004121122,0.001365719,0.0005274648,0.00187526,0.0005986094,0.001099155,0.008166975],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009371623,"about_ca_system_score_gemma":0.0005575545,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001385158,"about_ca_topic_score_gemma":0.0009283906,"domain_scores_codex":[0.9981636,0.000247494,0.00004515327,0.0002496314,0.001188937,0.0001052515],"domain_scores_gemma":[0.9988512,0.0001665585,0.00009011792,0.0001293931,0.0006567993,0.0001058946],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001412116,0.0004061564,0.001759453,0.00114719,0.0001015784,0.0002022955,0.0002988154,0.005489318,0.5130156,0.01675596,0.0535388,0.4058727],"study_design_scores_gemma":[0.00005986056,0.001366481,0.004285874,0.00009636781,0.00008705582,0.0008039774,0.0001007234,0.02142582,0.5916114,0.00114608,0.3788889,0.0001273915],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09340478,0.04199159,0.6284595,0.002828242,0.001336046,0.0006993011,0.006363522,0.02215625,0.2027607],"genre_scores_gemma":[0.2182427,0.01294123,0.674941,0.0006591173,0.000567581,0.000240775,0.007975597,0.002589002,0.08184305],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01332248,"threshold_uncertainty_score":0.04456812,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04434821248928673,"score_gpt":0.263424615975272,"score_spread":0.2190764034859853,"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."}}