{"id":"W4230315594","doi":"10.22215/etd/2005-07511","title":"Laser tweezers: a tool to assist self-assembly and template population","year":2005,"lang":"en","type":"dissertation","venue":"","topic":"Photonic Crystals and Applications","field":"Physics and Astronomy","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University; Canadian Heritage; Library and Archives Canada","funders":"","keywords":"Computer science","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00005942464,0.0002252152,0.00022844,0.00007344001,0.0001545735,0.0001336568,0.00009601206,0.0000890472,0.000473977],"category_scores_gemma":[0.000001137165,0.000217158,0.00007916673,0.0001288321,0.000003041946,0.0001072714,0.00001987681,0.0001311612,0.00009271754],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003691268,"about_ca_system_score_gemma":0.00004887551,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007050238,"about_ca_topic_score_gemma":0.0004712805,"domain_scores_codex":[0.9990306,0.000009599058,0.0002710603,0.0003570711,0.0001337631,0.0001978346],"domain_scores_gemma":[0.9994776,0.00002054198,0.0001203294,0.000229834,0.00005114148,0.0001005779],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.000157534,0.001846328,0.04336444,0.0003543505,0.001268742,0.00000381681,0.003568529,0.0002310504,0.02117806,0.1854644,0.04665351,0.6959093],"study_design_scores_gemma":[0.002457939,0.0002255011,0.5676194,0.0004379026,0.0008599027,0.000003692613,0.005903102,0.002750764,0.0230984,0.01000213,0.3827781,0.003863145],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9323108,0.00001599011,0.0003655285,0.00009196099,0.00007785521,0.0005019503,0.00008494128,0.00007810555,0.06647285],"genre_scores_gemma":[0.9821496,0.000003199925,0.002152898,0.00006169474,0.0002738364,0.000244168,0.002125788,0.00003482398,0.012954],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6920461,"threshold_uncertainty_score":0.8855448,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005943678518607409,"score_gpt":0.2684847420343854,"score_spread":0.262541063515778,"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."}}