{"id":"W2808975722","doi":"10.1117/12.2305409","title":"Design and test results of compact imaging spectrometer for chemical detection and identification","year":2018,"lang":"en","type":"article","venue":"","topic":"Spectroscopy and Laser Applications","field":"Chemistry","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"ABB (Canada)","funders":"","keywords":"Clutter; Spectrometer; Infrared; Imaging spectrometer; Remote sensing; Optics; Spectral signature; Identification (biology); Computer science; Hyperspectral imaging; Chemical imaging; Signature (topology); Environmental science; Physics; Artificial intelligence; Radar; Telecommunications; Geology; Mathematics","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":[0.001006436,0.0007644646,0.0006530577,0.0006288547,0.0002688891,0.000537861,0.001291486,0.0008118852,0.002636822],"category_scores_gemma":[0.00133563,0.0001998758,0.0003034625,0.0003255323,0.0003808071,0.0007763806,0.0003516627,0.0002066775,0.0008593652],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006425774,"about_ca_system_score_gemma":0.0004076737,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000754753,"about_ca_topic_score_gemma":0.0006474461,"domain_scores_codex":[0.9988164,0.0001584879,0.00004382823,0.000247478,0.0006330648,0.0001007847],"domain_scores_gemma":[0.9984741,0.0002499919,0.0001875069,0.0001956088,0.0007537843,0.0001390438],"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":[0.002357266,0.0004646909,0.008446569,0.0004077556,0.0001008951,0.0005117641,0.000346587,0.01055654,0.8807721,0.001718931,0.003092334,0.09122458],"study_design_scores_gemma":[0.0003514279,0.01030886,0.02295792,0.00003581237,0.0001932103,0.001251436,0.0001963619,0.08955405,0.8605275,0.0005052398,0.01403445,0.00008377346],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8039508,0.001378619,0.1775851,0.0004590731,0.0002488703,0.0004578838,0.000841756,0.00496351,0.01011438],"genre_scores_gemma":[0.940702,0.0001583066,0.05254618,0.0001364415,0.00004654121,0.0001429756,0.0005504626,0.0001748478,0.005542099],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002636822,"threshold_uncertainty_score":0.00882107,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01576539153955126,"score_gpt":0.2790345979717316,"score_spread":0.2632692064321804,"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."}}