Bibliographic record
Abstract
Each bidding contractors estimates his likely costs of carrying out the work detailed in the project schedules and adds a percentage markup to form the bid value. The value of the markup crucially influences the chances of a bidder winning the contract. Clearly, a low markup value should increases the chance of winning but decrease the profit, whilst a high markup should increase the profit but decrease the chance of winning the contract. It is very difficult for contractors to decide a proper markup, which happens to produce a satisfactory balance between the probability of winning the contract and the profit generated as a result of winning the contract. This paper presents a case-based reasoning decision support system (CBR-DSS) that assists contractors in solving markup estimation problem. The CRR-DSS uses successful cases of previous completed projects to derive solution to new project markup estimation problem. The principle of the CBR-DSS is to analogy new project with previous projects. Key Words: Case-Based Reasoning, DSS, Bidding, Markup Resume: Chaque contracteur demande estime son cout d’application d’un travail detaille dans les horaires et ajoute un percentage de maquillage pour avoir l’offre qui influence crucialement une eventuelle reussite d’un contrat. Evidemment une petite valeur de maquillage doit augmenter les chances de gagner mais reduire le profit tandis que un grand maquillage doit augmenter le profit mais reduire les chances d’arriver a un contract. Il est tres difficile pour les contracteurs de decider une offre convenable, qui eventuellement produit une balance de satisfaction entre la probabilite d’achever le contrat et le profit considere comme une reussite d’un contrat. Ce document presente un systeme du support decision rationnel base sur les cas (CBR-DSS) qui permet aux contracteurs de s’engager dans la solution des problemes estimes et demandes. Le CRR-DSS utilise des reussites de programmes pre-acheves qui servent a resoudre les problemes d’estimation dans un nouveau programme. Le principe de CBR-DSS est trouver les solutions pour de nouveaux programmes par analogie ceux pre-acheves. Mots cles: Raisonnement base sur les cas, DSS, offre, maquillage, acquisition Governmentale
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.019 | 0.007 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".