{"id":"W6888835595","doi":"10.22133/ijwr.2023.411727.1174","title":"Development of A Qr Code System for Tree Species Identification","year":2023,"lang":"en","type":"article","venue":"DOAJ (DOAJ: Directory of Open Access Journals)","topic":"QR Code Applications and Technologies","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"PricewaterhouseCoopers (Canada)","funders":"","keywords":"Scripting language; Identification (biology); Tree (set theory); JavaScript; Code (set theory); Web application","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":[0.003492721,0.0007596774,0.0008348253,0.001869587,0.000747791,0.00172017,0.001275267,0.001024084,0.02246279],"category_scores_gemma":[0.01217791,0.0004625473,0.0005753979,0.001283712,0.0006086494,0.002010373,0.001597226,0.001205054,0.01506452],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005145788,"about_ca_system_score_gemma":0.001973546,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00134212,"about_ca_topic_score_gemma":0.00112976,"domain_scores_codex":[0.9969937,0.0008166575,0.0004197465,0.0005135892,0.001059596,0.0001967024],"domain_scores_gemma":[0.9897727,0.002833035,0.0009172968,0.0009061782,0.005082542,0.0004881986],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001301165,0.0003906405,0.008201704,0.002478223,0.00008154106,0.001538263,0.002505471,0.003031041,0.0739932,0.0141051,0.09071937,0.8016543],"study_design_scores_gemma":[0.0005113644,0.002003297,0.01802934,0.001397767,0.0001856088,0.003746803,0.001457058,0.07668684,0.136526,0.0106402,0.7482481,0.0005675931],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02008268,0.0009822582,0.8830574,0.001354118,0.0009275061,0.006345863,0.005894891,0.05829585,0.02305942],"genre_scores_gemma":[0.08514019,0.0006625121,0.8754211,0.0007306266,0.0001912095,0.003491923,0.006091706,0.001943198,0.02632754],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02246279,"threshold_uncertainty_score":0.07514548,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.34113819963382,"score_gpt":0.5213031786373037,"score_spread":0.1801649790034837,"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."}}